kimas 2003 tutorial
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KIMAS 2003 Tutorial. The Craft of Building Social Agents. Henry Hexmoor University of Arkansas Engineering Hall, Room 328 Fayetteville, AR 72701. Content Outline. I. Introduction 1. History and perspectives on MultiAgent Systems 2. Architectural theories - PowerPoint PPT PresentationTRANSCRIPT
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KIMAS 2003 TutorialKIMAS 2003 Tutorial
Henry HexmoorHenry HexmoorUniversity of Arkansas
Engineering Hall, Room 328
Fayetteville, AR 72701
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Content Outline
I. Introduction1. History and perspectives on MultiAgent Systems 2. Architectural theories3. Agent Oriented Software Engineering
II. Social agents4. Sociality and social models5. Dimensions for Developing a Social Agent Examples in Autonomy, Trust, Social Ties, Control, Team, Roles, Trust, and Norms
6. Agent as a member of a group...Values, Obligations, Dependence, Responsibility, Emotions
III. Closing
7. Trends and open questions8. Concluding Remarks
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Definitions
1. An agent is an entity whose state is viewed as consisting of mental components such as beliefs, capabilities, choices, and commitments. [Yoav Shoham, 1993]
2. An entity is a software agent if and only if it communicates correctly in an agent communication language. [Genesereth and Ketchpel, 1994]
3. Intelligent agents continuously perform three functions: perception of dynamic conditions in the environment; action to affect conditions in the environment; and reasoning to interpret perceptions, solve problems, draw inferences, and determine actions. [Hayes-Roth, 1995]
4. An agent is anything that can be viewed as (a)Perceiving its environment, and (b) Acting upon that environment [Russell and Norvig, 1995]
5. A computer system that is situated in some environment and is capable of autonomous action in its environment to meet its design objectives. [Wooldridge, 1999]
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Agents: A working definition
An agent is a computational system that interacts with one or more counterparts or real-world systems with the following key features to varying degrees:
• Autonomy
• Reactiveness
• Pro-activeness
• Social abilities
e.g., autonomous robots, human assistants, service agents
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
The need for agents
1. Automation of dirty, dull, and dangerous as well as tedious, boring, and routine tasks to relieve humans of such duties. E.g., desktop assistants or intelligent in service of humans.
2. An improved human sense of “presence” for humans collaborating in physically disparate locations. E.g., knowledge management tasks like war-rooms and human users benefit from agents who proxy for their human counterparts.
3. Democratization of computing, services, and support. E.g., functions such as the department of motor vehicles or public libraries and virtual museums.
4. Reduction of redundancy and overlap due to competition. E.g., tracking and sharing power or telecommunication services.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Agent Typology
• Person, Employee, Student, Nurse, or Patient• Artificial agents: owned and run by a legal entity • Institutional agents: a bank or a hospital• Software agents: Agents designed with software• Information agent: Data bases and the internet• Autonomous agents: Non-trivial independence • Interactive/Interface agents: Designed for
interaction• Adaptive agents: Non-trivial ability for change• Mobile agents: code and logic mobility
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Agent Typology
• Collaborative/Coordinative agents: Non-trivial ability for coordination, autonomy, and sociability
• Reactive agents: No internal state and shallow reasoning
• Hybrid agents: a combination of deliberative and reactive components
• Heterogenous agents: A system with various agent sub-components
• Intelligent/smart agents: Reasoning and intentional notions
• Wrapper agents: Facility for interaction with non-agents
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Crafting a Social Agent
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Falacies: What Agent-based Systems are not
• Computational X where X is from the social sciences such as the economics
• Agents are not middleware components• Agents are not Grid Services• Agents are not Internet software • Agents need not dwell online• Agent-based Systems are not necessarily decision-
support systems• Agent-based Systems do not necessarily employ AI
methods• Agents need not be implemented in specific
programming languages or paradigms
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Multi-agency
A multi-agent system is a system that is made up of multiple agents with the following key features among agents to varying degrees of commonality and adaptation:
• Social rationality
• Normative patterns
• System of Values
e.g., eCommerce, space missions, Intelligent Homes
The motivation is coherence and distribution of resources.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Summary of Business Benefits
• Modeling existing organizations and dynamics
• Modeling and Engineering E-societies
• New tools for distributed knowledge-ware
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Two views of Multi-agency
Constructivist: Agents are rational in the sense of Newell’s principle of individual rationality. They only perform goals which bring them a positive net benefit without regard to other agents. These are self-interested agents.
Sociality: Agents are rational in the Jennings’ principle of social rationality. They perform actions whose joint benefit is greater than its joint loss. These are self-less, responsible agents.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Multi-agent assumptions and goals
• Agents have their own intentions and the system has distributed intentionality
• Agents model other agents mental states in their own decision making
• Agent internals are of less central than agents interactions
• Agents deliberate over their interactions
• Emergence at the agent level and at the interaction level are desirable
• The goals is to find some principles-for or principled ways to explore interactions
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Abstract Architecture
action
Environment
actionsstates action
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Architectures
• Deduction/logic-based
• Reactive
• BDI
• Layered (hybrid)
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Abstract Architectures
An abstract model: <States, Action, S*A>
An abstract view
S = {s1, s2, …} – environment states
A = {a1, a2, …} – set of possible actions
This allows us to view an agent as a function
action : S* A
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Logic-Based Architectures
These agents have internal state See and next functions and model decision making by a set of deduction rules for inference
see : S Pnext : D x P Daction : D A
Use logical deduction to try to prove the next action to take Advantages
Simple, elegant, logical semantics Disadvatages
Computational complexityRepresenting the real world
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Reactive Architectures
Reactive Architectures do not use symbolic world model
symbolic reasoning
An example is Rod Brooks’s subsumption architecture Advantages
Simplicity, computationally tractable, robust, elegance Disadvantages
Modeling limitations, correctness, realism
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
BDI: a Formal Method
• Belief: states, facts, knowledge, data
• Desire: wish, goal, motivation (these might conflict)
• Intention: a) select actions, b) performs actions, c) explain choices of action (no conflicts)• Commitment: persistence of intentions and trials
• Know-how: having the procedural knowledge for carrying out a task
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Beliefs
beliefrevision
generateoptions
Desiresfilter
Intentions
actsense
Environment
Belief-Desire-Intention
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
A simplified BDI agent algorithm
1. B = B0;
2. I := I0;
3. while true do
4. get next percept ;
5. B := brf(B, ); // belief revision
6. D:=options(B,D,I); // determination of desires
7. I := filter(B, D, I); // determination of intentions
8. := plan(B, I); // plan generation
9. execute
10. end while
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Correspondences
• Belief-Goal compatibility:
Des Bel
• Goal-Intention Compatibility:
Int Des
• Volitional Commitment:
Int Do Do
• Awareness of Goals and Intentions:
Des BelDes
Int BelInt
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Layered Architectures
Layering is based on division of behaviors into automatic and controlled.
Layering might be Horizontal (I.e., I/O at each layer) or Vertical (I.e., I/O is dealt with by single layer)
Advantages are that these are popular and fairly intuitive modeling of behavior
Dis-advantages are that these are too complex and non-uniform representations
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Crafting a Social Agent
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Agent-Oriented Software Engineering
AOSE is an approach to developing software using agent-oriented abstractions that models high level interactions and relationships.
Agents are used to model run-time decisions about the nature and scope of interactions that are not known ahead of time.
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Crafting a Social Agent
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AOSE Considerations: Track 1
Programming platforms (e.g., JACK) to support not just programming and design
What, how many, structure of agent?
Model of the environment?
Communication? Protocols? Relationships? Coordination?
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
AOSE Considerations: Track 2
Extending UML to support agent communication, negotiation etc.
Communication? Protocols? Relationships? Coordination?
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Gaia- Wooldridge, et al
The Analysis phase: Roles model:
- Permissions (resources) - Responsibilities (Safety properties and Liveliness properties)
- Protocols Interactions model: purpose, initiator, responder, inputs,
outputs, and processing of the conversationThe Design phase:
Agent modelServices modelAcquaintance model
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Crafting a Social Agent
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Scott DeLoach’s MaSE
Roles TasksSequenceDiagrams
Agent ClassDiagram
Internal AgentDiagram
ConversationDiagram
DeploymentDiagram
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Crafting a Social Agent
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Break– 5 minutes
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Content Outline
I. Introduction1. History and perspectives on MultiAgent Systems 2. Architectural theories3. Agent Oriented Software Engineering
Break 5 minutes II. Social agents
4. Sociality and social models5. Dimensions for Developing a Social Agent Examples in Autonomy, Trust, Social Ties, Control, Team, Roles, Trust, and Norms
Break 5 minutes6. Agent as a member of a group...Values, Obligations, Dependence, Responsibility, Emotions
III. Closing
7. Trends and open questions8. Concluding Remarks
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Crafting a Social Agent
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A Multiagent System Top level loop
Initialize Groups, InterconnectionsFor agents 1- n { While (1) { Sense (self, world, others)
Reason (self, others)Act (physical, speech, social)
}}
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Inside an agent…
While (1) { Sense (self, world, others)
Determine attitude (self, others)Reason (self, others)Act (physical, speech, social)
}
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Crafting a Social Agent
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What is Sociality?
Think, Feel, Do Think, Feel, Do
Think, Feel, Do Think, Feel, Do
• In interactions one individual’s thinking, feeling, and/or doing affects another individual.
• “” may involve a social action, a social convention, and a personal rationality.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
What is Sociality?
Think, Feel, Do Think, Feel, Do
Think, Feel, Do Think, Feel, Do
• An individual may engage collectives in interaction of thinking, feeling, and/or doing.
• “” may involve a social action, a social convention, and a unit rationality.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
What is Sociality?
Think, Feel, Do Think, Feel, Do
Think, Feel, Do Think, Feel, Do
• An agent may engage a human in interaction of thinking, feeling, and/or doing.
• “” may involve a social action, a social convention, and a personal rationality.
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Crafting a Social Agent
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What is Social Action?
• Social actions produce different kinds of influences.
• For example actions involving Resources, Delegation, Permission, Help, and Service.
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Crafting a Social Agent
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What is Social Convention?
• Social conventions prescribe transformations of social influences as well as shifts and changes in the transformations.
• Examples:• Interpersonal tactics such as reciprocity, scarcity, and
politeness.• Use of norms, values, plans, policies, protocols, and roles.• Following a conversational policy. • Emotional reactive responses• Cooperation logics• Adaptations and emergence rules
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What is Personal/Unit Rationality?
• Personal/unit Rationality prescribes stance of an individual or a collective toward social conventions with respect to others.
• An agent/collective might choose to follow or abandon social conventions either with all agents or selectively.
• Social Rationality versus Individual Rationality
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Putting it together (CEBACR): A social model of interaction
<Cognition,Emotions, Behaviors,
Social Actions, Social Conventions,
Personal/Unit Rationality, Embodiment>
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A Special Case of Do Do Sociality
• [Do] [Do]
• Actions are “buy” and “sell”• Social Conventions are conventions of bartering.• Personal/Unit Rationality is accounting for utilities of self or
others. This can be simple or extend to issues of reciprocity and goodwill.
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A Social Agent
• An agents that has to interact with people, other agent(s), where it is affected and can affect others’ cognitive states, emotions, and/or behavior via social actions, social conventions, a personal rationality.
• Generally, such agents are more complex than reactive agents and must include social perception in their deliberation.
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A Social Agent
• We cannot merely add social modules to prefabricated agents. Social makeup of such agents are found in all aspects of their architecture and must be designed from the start.
• We must at least have access to an agent’s social model:
<Cognition, Emotions, Behaviors, Social actions, Social Conventions, Personal Rationality>
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Crafting a Social Agent
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A Social Agent
Socially intelligent agents are biological or artificial agents that show elements of (humanstyle) social intelligence. The term artificial social intelligence refers then to an instantiation of human-style social intelligence in artificial agents. (Dautehahn 1998)
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Social Inference
Observing Interpersonal ExchangesGesture
Body Language
Emotions in communicationIllocution in communication
Goals and plans
Commonalities in goals and plans
BenevolenceSocial ties Psychological states
Inferred Attitudes and Relationships
Inferred Social Import Trust AutonomyPower CoherenceNorms ValuesTeam Control
Sub-cognitive
Cognitive
AttitudeCapability
Dependence
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Situatedness
• Physically situatedness promotes frequent sampling of physical environment, feedback via physical environment… as in the Subsumption architecture
• Socially situatedness promotes frequent sampling of environment (gossip), feedback via social interaction… to new agent architectures
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Crafting a Social Agent
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Levels of Sociality
• There are many MAS or HAI problems that are deterministic and would not require social reasoning. I.e., agent’s actions would not depend on others and if so it is pre-determined. At best, sociality is a luxury.
• There are scenarios where sociality, explicit reasoning about other agent’s or human actions are critical and it is not all predetermined. This requires high level of sociality.
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Crafting a Social Agent
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Social delegation
• E.g., X gives Y permission and authority to make decisions for their organization
• Social delegation differs from physical delegation in that agents will have a “cognitive” exchange in stead of a physical one.
• Models of social delegation might be economic (utilitarian), dependency (in-debtedness), power-based (authority), or democratic.
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Crafting a Social Agent
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Social Environment
Tasks;Resources; Ontologies
Public skills
Communication and exchange
Modeling other agents …
Social and collaborative notions
Emotions
Initiative, Autonomy, Power, Control, …
AnthropomorphismLanguage realism
Collaboration: Trust, safety, flexible roles, policies, preferences
Emotions
Awareness…
Emergent Norms and roles
Cultural shifts in institutions organizations
Adherence to norms, values, obligations, power, org rules…
Adaptation and changesin reasoning about basic social notions
HumanOrganization
Culture Multi-Agent
Dimensions for Developing a Social Agent
Communication and exchange
Planning and learning abilities
Team
Community
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Crafting a Social Agent
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Social Environment
HumanOrganization
CultureMulti-Agent
Dimensions for Developing a Social Agent
Team
Community
Asynchronous : Sit Aware : Real-timeCommunication
Info sharingCoordination
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Crafting a Social Agent
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Social Environment
Agents that are embedded in social environments must be designed to account for the following needs:
• Social tasks• Shared Resources • Ontologies• Public skills related to tasks and resources such as
requesting and delegating
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Crafting a Social Agent
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Agents in Public Service
Interactions with the public beyond individuals
Public libraries Museums Shopping malls Transportation stations Billboards and road signs
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Multiagent
Agents that can relate to other agents must be designed to account for the following needs:
• Communication and exchange of information,• Modeling other agents and rationality: altruism and benevolence,• Planning and learning abilities,• Social and collaborative notions: Autonomy, Values, Norms,
Obligations, Dependence, Control, Responsibility, Roles, Preference, Power, Trust, Teaming, Persona.
• Emotional communication.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Agents in automation of dirty, dull, and dangerous tasks
Intelligent homes Factories Telecommunications Power Plants Investment Transportation Electronic Customer Relations Management Cross Organizational Relations
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Multiagent: Shared Autonomy Among Personal Satellite Assistants
PSAs reason about commitments to teaming to respond to alarms
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Autonomy Sources
Capability
Social ties… benevolence, permissions, peer pressure (autonomy norm), reciprocity, norm sanctions
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Trust Can mean different things
Expectation of partner’s competence- Cristiano Castelfranchi
Expectation of partner’s benign intent- Diego Gambetti
Trust as a reputation and a recommendation- Mike Schillo
Correct Expectations about partner’s actions- Patha Dasgupta
Trust as reliable contract- Svet Brainov
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Social Ties
Social ties between agents affects social relationships. Trust and autonomy are increased with stronger ties. Communities are more robust with ties. Network structures embody collective properties of their
community.
Number of ties
Performance
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Models of Trust and Autonomy 2002
Trusting value(A, B, t) = Capability(B, t) + Benevolence(B, A, t) + Delegation harmony(A,B)Autonomy value (A, t) = Capability(A, t) + Average Trust (A) + Balance of reciprocity()
0
2
4
6
1 8 15 22
Time
Ave
rage
Tru
st &
A
vera
ge A
uton
omy
Tb
Ab
An
Tn
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Terraforming Mars 2002
Trust(Aj, Ak, t) = Trust(Aj, Ak, t-1) – (rate * Trust(Aj, Ak, t-1) + (rate * (gain - investment))
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Human
Agents that can relate to humans socially must be designed to account for the following needs:
• Communication and exchange of information,• Human intent and preferences, • Human need for anthropomorphic appeal,• Nested representations of humans and agents,• Human policies for interaction and guidance,• Collaborative requirements, and• Emotional communication
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Trust
Reasons for trust in agents:
Preference to delegate: an human operator might want another agent who has more time or resources to carry out a task
Human-agent relations: Agents can use human their understanding of human models of trust to interact with humans
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• Human-Agent Interaction
• Adjustable Autonomy
Autonomy
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HAI: Shared Autonomy between an Air Traffic Control assistant agent and the human operator
ATC agent and human operators learn to share and trade autonomies
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HAI: UCAV formations
•UCAVs reason about helping in attack situations •HA power
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Organization
Agents that must operate in organizations must be designed to account for the following needs:
• Awareness of organizational rules, and structure, • Ability to evolve and recognize emergent norms and roles,
and• Adaptation and changes in reasoning about basic social
notions.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Knowledge Management
Data storage and retrieval functions Indigenous ontologies Norms and Policies Institutions
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Norms
• Involve two or more agents. Each agent understands and shares them.
• Agents have power to not choose them.
• There is no direct rational account of them available to the agents.
• The bearer experiences an implicit or an explicit sanction or rewards for adoption.
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City grid - 2003
• Collisions cost agents time and intersections are out for a period.• Agents must reason about norms of stopping for traffic lights or not based on comparisons of their gains and losses relative to the society• Adaptive norm revision outperforms prescriptive norm assignment
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Multiagent: Shared Autonomy Among Low-orbit Satellites
Satellites learn to recruit and form teams for collaborative image gathering
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Roles
• Several agents can adopt it individually, independently, and concurrently. One agent may adopt several simultaneously. Several agents may adopt it as a group. In general we will call this the adopter.
• It is meaningful in the social context of other agents including (a) the adopter’s relationship to other agents and groups, (b) the agent’s mental attitudes about the social relationships, and (b) the available norms including obligations and responsibilities.
• There are typical capabilities associated with the adopter. If the adopter loses these abilities then the efficacy of the role is jeopardized.
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Roles
• Networks of roles are more clearly seen in role-based access control.
• Role hierarchy and role grouping are useful for selecting subsequent roles [Moffett and Lupu, 1999, Na and Cheon, 2000].
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Culture
Agents that are culturally embedded must be designed to account for the following needs:
• Ability to reason about adherence to norms, values, obligations, organizational rules, etc., and
• Ability to recognize shifts in culture of their organizations and institutions
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Agent Historians and Dictionaries
Nuances of cultural shifts Norms Laws Institutions
Collaborative filtering
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Break– 5 minutes
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Content Outline
I. Introduction1. History and perspectives on MultiAgent Systems 2. Architectural theories3. Agent Oriented Software Engineering
Break 5 minutes II. Social agents
4. Sociality and social models5. Dimensions for Developing a Social Agent Examples in Autonomy, Trust, Social Ties, Control, Team, Roles, Trust, and Norms
Break 5 minutes6. Agent as a member of a group...Values, Obligations, Dependence, Responsibility, Emotions
III. Closing
7. Trends and open questions8. Concluding Remarks
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Agent as a member of a group...
agent
group
values(terminal goals)
norms
partakes
relies on
member of
goalsspecifies
plans
obligations
honors
institution
organization
inheritspartakes set/borrow contains
shares
handles
partakes
roles
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Values
• "value" might mean:(a)assessment of usefulness of an object or
action relative to a purpose, I.e., "(instrumental) evaluations", E.g., ="this knife is good for chip carving ",
(b) absolute assessment of desirability of something, I.e, “principles”, E.g., "honesty is good"
• Adding value to an agent enables it to generate internal desires as well as adds a level of behavior predictability for other agents.
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Obligations
• Obligations capture all forms of social influence.
• Obligations have a strong deontological and motivational senses (more so than norms)
• Obligations are frequently assumed to have penalties associated with the failure to meet the obligation. We make no such assumption; some obligations may have sanctions and some may not.
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Responsibilities
• There are several types of responsibility: (a)Responsibility to concerns an agent’s obligation
to perform an action. (b)Responsibility for concerns an agent’s
obligation to see that a state of affairs obtains. (c) Responsibility about is the agent’s obligation to
behave in accordance with its principles, which is general, abstract, and typically with respect to an agent’s immutable values.
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Responsibilities, CAST project [Yen, et al. 2001]
•Agents are represented as nodes of a graph.
•One type of labeled directed edge is between two agents (A B), and it represents that A delegates to B or conversely B is responsible to A with respect to .
•The delegation relationships is non-reflexive, anti-symmetric, and transitive. The transitive property can be used to establish implied relationships.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Obligationsab (i.e., responsibility)
Values Norms
Dependenceba
(Powerab , Controlab)
Autonomy
Delegationba
Trustba
Emerson, 1962Tuomela, 2000
Tuomela, 2000
Mayer, et al1995
The big picture
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Emotions
Emotions provide possibilities for bypassing chains of reasoning to protect the agent in dangerous situations or to enable it to work with agents that have not been beneficial in the past.
HAI: quick feedback by human or agent; human appeal
Multiagent: Appraisal of situations
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Emotions
Emotions Theories: correspondence between emotions and behavioral situations. Feeling good a or bad into emotions…
Personality Theories: Individual differences that affect emotional relationships
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Content Outline
I. Introduction1. History and perspectives on multiagents 2. Architectural theories3. Agent Oriented Software Engineering
Break 5 minutes II. Social agents
4. Sociality and social models5. Dimensions for Developing a Social Agent Examples in Autonomy, Trust, Social Ties, Control, Team, Roles, Trust, and Norms
Break 5 minutes6. Agent as a member of a group...Values, Obligations, Dependence, Responsibility, Emotions
III. Closing
7. Trends and open questions8. Concluding Remarks
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Content Outline
I. Introduction1. History and perspectives on multiagents 2. Architectural theories3. Agent Oriented Software Engineering
II. Social agents4. Sociality and social models5. Autonomy, Team, Values, Norms, Obligations, Dependence, Control, Responsibility, Roles, Trust, Emotions
III. Closing6. Trends and open questions7. Concluding Remarks
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Current Trends
Pervasive and emerging agent applications: agent mediated e-commerce, emotional agents, embodied agents, virtual characters, conversational agents, etc.
Standardization efforts: FIPA.
New Initiatives: semantic web initiative.
Agent tournaments: RoboCup, Trading Agent Competition.
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Concluding Remarks
There are many uses for Agents: These are highly intuitive and expressive Multiagent Systems: These provide methods for defining
institutions and working models of sociological theories
Many open problems area available Theoretical issues for modeling social elements such as
autonomy, power, trust, dependency, norms, preference, responsibilities, security, …
Adaptation and learning issues Communication and conversation issues
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Further Explorations
[email protected] Agents.umbc.edu http://www.AgentLink.org/ http://www.multiagent.com/ http://homepages.feis.herts.ac.uk/~comqkd/aaai-social.html
http://jasss.soc.surrey.ac.uk/5/4/4.html http://jom-emit.cfpm.org/ http://www.stephenmarsh.ca/ http://www.iiia.csic.es/ http://www.salford.ac.uk/cve/va99/on-line99.htm
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Crafting a Social Agent
September 30, 2003KIMAS 2003 Tutorial
Hexmoor
Further Explorations
http://orgwis.gmd.de/projects/SocialWeb/ http://bruce.edmonds.name/ssi/ http://www.casos.ece.cmu.edu/home_frame.html
http://bruce.edmonds.name/sfs/ http://jasss.soc.surrey.ac.uk/4/1/contents.html
http://www.isi.edu/teamcore/ http://www.ecs.soton.ac.uk/~nrj/soc-rat.html