1 analysing system-user cooperation in kads h. p. de greef and j. a. breuker, department of social...

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1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge Acquisition (1992) 4, 89-108 Rubén Lara

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Page 1: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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Analysing system-user cooperation in KADS

H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge Acquisition (1992) 4, 89-108

Rubén Lara

Page 2: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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Introduction

- Motivation:• KBS may take the role of intelligent, active agent.• Specification of how the user and the agent cooperate becomes important.• In knowledge engineering there are no methods which allow a specification

of the role of a system by successive refinement• From the WSMO view point, successive refinement can (and should)

be used for the definition of goals and service capabilities• Goal reuse and refinement• Services defined by using other available services

Page 3: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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Functions, cooperations and communication

Cooperation is based upon:• A distribution of tasks: Task decomposition in which sub-tasks are assigned

to different agents (commitment, an agent may only be committed to a particular subgoal)• In WSMO, orchestration of the service. Service commitments

(capabilities) are matched against requested tasks (goals) statically (wwMediator) or dynamically (goal)

• Dependencies: A network of dependencies where one sub-task may require the output of another sub-task as an input. • In WSMO, this is the data flow that has to be specified in the

orchestration (externally visible in the choreography).

• Control: Agents must at least know which subtasks they have to perform when• This is the case for the service declaring the orchestration, while the

services used work on request

Page 4: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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Functions, cooperations and communication (II)

• Fixed task distribution + specification of dependencies and control = model of cooperation• Orchestration

• In DAI, autonomous agents propose and negotiate a task decomposition or distribution (similar to negotiating and planning)• Can be done for goals in the orchestration

Page 5: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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Functions, cooperations and communication (III)

Analysis of cooperation (intelligent automation of some functions)

• An emcompassing real-world task is the starting point for creating a task model• Goal (capability)

• Decomposition of the task, identification of interdependencies among sub-tasks, distribution of sub-tasks over the agents (system and user types)• Orchestration, (dynamic) distribution, only system agents considered

• Refinement of the task model into a model of cooperation. It adds a specification of the control that is needed to synchronize system activity and user activity• Choreography

Page 6: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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The task model: decomposition and distribution

• Assignment to users and systems• Only systems explicitly considered

• Heuristics for task decomposition• Object decomposition: Parts in the output, each of the parts may be

from a different subtask• Object refinement: Levels of abstraction in the output, sub-tasks may

consist of a sequence of refinement steps• Functional sequencing: Sequence of operation or transformations on

the same object• Knowledge typing: Knowledge required “strongly typed”, it may suggest

a decomposition according to the type of knowledge required• Heuristics that can be considered when defining task decomposition

Page 7: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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The task model: decomposition and distribution (II)

• Not always unique assignment of sub-tasks• Insufficient refinement• Dynamic assignments (WSMO dynamic composition)• Parallel sub-tasks (system and user)• Instruction and execution (two agents)

Page 8: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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The cooperation model

• Elements transferred between sub-tasks• Information (specific states in the world or in the mind)• Knowledge (explanation or teaching purposes) / not in WSMO• Skill (instruct other agent o how to perform sub-task) / not in WSMO

• Additional transfer task: negotiate• Transferring information about the negotiation or the problem solving

• Will be considered in WSMO-Full

• Another relevant aspect• Accessibility to information: whether the user really has access to the

necessary information• Essential and missing in WSMO!!!

Page 9: 1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge

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Conclusions

• WSMO is fulfilling most of the requirements/methods presented in KADS and relevant to the domain

• Specification of goals, capabilities, orchestration and choreography is a delicate task, and some methodology could be reused/developed

• An essential aspect, the information a user can (and want) to disclose for a service request, is not modelled in WSMO, as well as assumptions fulfilled

• Define KBs with a scope?