The ecology of action selection: insights from artificial life
Authored by Anil K Seth
Date Published: 2007
DOI: 10.1098/rstb.2007.2052
Sponsors:
United Kingdom Engineering and Physical Sciences Research Council (EPSRC)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
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Mathematical description
Model Code URLs:
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Abstract
The problem of action selection has two components: what is selected and
how is it selected? To understand what is selected, it is necessary to
distinguish between behavioural and mechanistic levels of description.
Animals do not choose between behaviours per se; rather, behaviour
reflects interactions among brains, bodies and environments. To
understand what guides selection, it is useful to take a normative
perspective that evaluates behaviour in terms of a fitness metric. This
perspective, rooted in behavioural ecology, can be especially useful for
understanding apparently irrational choice behaviour. This paper
describes a series of models that use artificial life ( AL) techniques
to address the above issues. We show that successful action selection
can arise from the joint activity of parallel, loosely coupled
sensorimotor processes. We define a class of AL models that help to
bridge the ecological approaches of normative modelling and agent- or
individual- based modelling ( IBM). Finally, we show how an instance of
apparently suboptimal decision making, the matching law, can be
accounted for by adaptation to competitive foraging environments.
Tags
Model
ideal free distribution
perspective
Choice
Decision
Foraging behavior
Complex
Reinforcement
Basal ganglia
Matching law