tamas soton 2008
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Tamás Makány
www.tamasmakany.comFaculty Postgraduate Conference - Southampton, 2008 June
University of Southampton, UK
Optimizations in Spatial Cognition:
Strategies and Trade-offs
Overview
Optimality in Spatial Cognition Spatial Abilities, Trade-off, Exploratory Strategies
Empirical Studies Experiment I.: Physical Environment
Experiment II.: Agent-based Simulation
Overall Summary
Optimality in Spatial Cognition
Spatial Cognition involves skills that enables us to : interact effectively and efficiently with our environment
(Theoretical) Optimum
‘do the best possible’
Behavioural Optimum
‘do the best you can’
increasespatial
knowledge(memory)
reducetravel
distance(energy)
Optimization
find the target with minimal effort
exploratory strategies ?
Overview
Optimality in Spatial Cognition Spatial Abilities, Trade-off, Exploratory Strategies
Empirical Studies Experiment I.: Physical Environment
Experiment II.: Agent-based Simulation
Overall Summary
Research question & hypotheses 1.
RQ: What are the cognitive and behavioural factors that influence spatial exploration?
Hy1: Humans explore novel physical environments differently, according to how they optimize their spatial cognition:
increase spatial knowledge (memory) extensive exploration reduce distance travelled (energy) limited exploration
Hy 2: Humans are optimizing their explorations in terms of a trade-off b/w:
spatial memory distance travelled
Experiment I. – Physical Environment
Experimental Design
41 participants; 2 omitted 24 female; 17 male3.5m x 3.5m squared spaceblack curtain on the walls5 objects in boxes to explore
3 phases:- Free exploration* - Learning- Navigation test
2 measures of navigation:- extendedness of routes (memory)- distance travelled (energy)
Makany, T., Redhead, E., & Dror, I. E. (2007). Spatial exploration patterns determine navigation efficiency: Trade-off between memory demands and
distance travelled. QJEP, 60, 1594-1602.
Experiment I. – Physical Environment
Results-2 initial exploratory strategies were found:
Memory Distance
extensive exploration(higher memory
demands)
shorter overall distance travelled
(lower energy cost)
limited exploration(lower memory
demands)
longer overall distance travelled
(higher energy cost)
Makany, T., Redhead, E., & Dror, I. E. (2007). Spatial exploration patterns determine navigation efficiency: Trade-off between memory demands and
distance travelled. QJEP, 60, 1594-1602.
(n=28) (n=11)
Experiment I. – Physical Environment
Summary
we found 2 distinct patterns of exploration: axial & circular
these patterns seem to reflect on different spatial optimization strategies:
spatial knowledge (memory) optimization travelled distance (energy) optimization
interaction of navigation performances suggests a trade-off between memory & distance strategies
Further Steps
empirically test whether the manipulation of these exploratory strategies result in optimization trade-off
build a computational model to simulate human spatial exploratory behaviour Makany, T., Redhead, E., & Dror, I. E. (2007). Spatial exploration patterns
determine navigation efficiency: Trade-off between memory demands and distance travelled. QJEP, 60, 1594-1602.
Overview
Optimality in Spatial Cognition Spatial Abilities, Trade-off, Exploratory Strategies
Empirical Studies Experiment I.: Physical Environment
Experiment II.: Agent-based Simulation
Overall Summary
Research question & hypothesis 2.
RQ: What are the cognitive and behavioural factors that influence spatial exploration?
Hy3: Human exploratory behaviour can be simulated by using simple optimization strategies
follow/avoid known routes (memory-strategy) extensive exploration
minimize/maximize overall distance travelled (energy-strategy) limited exploration
Hy 4: Our model will reproduce the same trade-off as in humans b/w:
spatial memory distance travelled
Experiment 2. – AB Simulation
Agent-based model in NetLogoSingle artifical agent per run 2D 6x6 grid square lattice
space5 objects to explore
Task: visit all objects based on an object cost function:
ei,j = distance to object j from position im = steps already taken on the wayα= parametre weight (complementary)
121 test runs; full parametrization
2 measures of navigation:- extendedness of routes
(memory)- distance travelled (energy)
€
f (d) = (ei, jα )×(m1−α )
Makany, T., & Makowsky, M. (submitted). Human spatial exploratory strategies in an agent-based model: Trade-off between distance and memory demands. Spatial
Cognition Conf., Freiburg (Germany).
Experiment 2. – AB Simulation
Results-2 exploratory strategies were found:
extensive exploration(higher memory
demands)
limited exploration(lower memory
demands)
longer overall distance travelled
(higher energy cost) Memory Distance
shorter overall distance travelled
(lower energy cost)
Circular (n=84) Axial (n=35)
Makany, T., & Makowsky, M. (submitted). Human spatial exploratory strategies in an agent-based model: Trade-off between distance and memory demands. Spatial
Cognition Conf., Freiburg (Germany).
Memory Distance
Memory Distance
Experiment 2. – AB Simulation
Summary
we found 2 patterns of exploration, similar to Exp. 1.: axial & circular
simulation results confirmed the strategy optimization trade-off
Further Research
test the model with other environmental parameters (e.g., virtual)
Makany, T., & Makowsky, M. (submitted). Human spatial exploratory strategies in an agent-based model: Trade-off between distance and memory demands. Spatial
Cognition Conf., Freiburg (Germany).
Overview
Optimality in Spatial Cognition Spatial Abilities, Trade-off, Exploratory Strategies
Empirical Studies Experiment I.: Physical Environment
Experiment II.: Agent-based Simulation
Overall Summary
Overall Summary
Spatial Cognition involves skills that enables us to :
interact effectively and efficiently with our environment
increasespatial
knowledge(memory)
reducetravel
distance(energy)
Optimization
find the target with minimal effort
exploratory strategies ?
RQ: What are the cognitive and behavioural factors that influence spatial exploration?
- Hy1: Humans explore novel physical environments differently, according to how they optimize their spatial cognition- Hy 2: Humans are optimizing their explorations in terms of a trade-off- Hy3: Human exploratory behaviour can be simulated by using simple optimization strategies
- Hy 4: Our model reproduced the same trade-off as in humans
✔
✔
✔
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Overall Summary
Impact of Research
Theoretical :
- how the human cognitive system optimizes information when exploring novel spaces
- individual differences between good/poor explorers
- cognitive/behavioural efficiency
Applied :
- predict spatial performances based on initial exploratory behaviours
- aid poor explorers from a very early phase of their spatial learning
- spatial design applications in multiple environments
Tamás Makány
www.tamasmakany.comFaculty Postgraduate Conference - Southampton, 2008 June
University of Southampton, UK
Optimizations in Spatial Cognition:
Strategies and Trade-offs
Thank you!
AcknowledgementsDr. Edward Redhead – University of SouthamptonDr. Itiel Dror – University of SouthamptonDr. Anne McBride – Univerisity of Southampton*T.M. was supported by the School of Psychology PhD Scholarship
Cluster Analysis Dendrogram I.
Cluster Analysis Dendrogram 2.