Simulating the Behaviour of Adaptive Agents

1. Simulating the Behaviour of Adaptive Agents David F Batten Coordinator CSIRO Agent-Based Modelling Working Group (CABM)

2. Boundedly Rational Humans • In the social and economic sciences, most modellers rely heavily on certain simplifying assumptions: e.g. homogeneity of actorsperfect, logical, deductive rationalitystatic equilibria. • Most of game theory and general equilibrium theory are still based on these assumptions. • Many social scientists admit that these assumptions are unrealistic. Herbert Simon’s notion of satisficing made it clear that our rationality is boundedin more complicated situations.

3. Complicated Situations • In highly-complicated, interactive situations, human agentscannot rely on other human agentsto behave or respond in a perfectly rational manner. • Instead they must guess each other’s behaviour. • This lands us in a world of subjective beliefs, and subjective beliefs about subjective beliefs. • Objective, well-defined, shared assumptions cease to exist. Thus rational, deductive reasoning cannot apply because the problem has become ill-defined.

4. A “Bottomless” Ocean SIMPLE TIC-TAC-TOE CHECKERS (DRAFTS) CHESS or GO COMPLICATED

5. Human Reasoning • How do human beings actually reason in situations that are complicated or ill-defined? • Modern psychology tells us that we are moderately good at deductive logic, thus we make only moderate use of it. On the other hand, we are superb at seeing, recognizing or matching patterns. • In complicated situations, we look for patterns, then simplify the problem using these patterns to construct temporary hypotheses or mental models to work with. We carry out localized deductions based on these mental models, and then we act on them.

6. Adaptive Behaviour • Feedback from the system’s performance serves to strengthen or weaken our beliefs in our current mental models, causing us to discard or replace them (e.g. if they do not lead to satisfactory outcomes). • As Tom Sargent suggests, if we lack full definition of any problem, then we devise simple mental models to “paper over” the gaps in our understanding. • Such behaviour is not deductive, but inductiveandadaptive(see Holland et al, 1986 or Arthur, 1994). • We can see adaptive behaviour at work in Chess.

7. Chess Playing Pattern Formation Pattern Recognition Observe opponent’s move and search for possible patterns Discern “chunks” or “patches” of familiar moves Strategy Selection Select your next move Local Deduction Hypothesis Selection Deduce your mental model to counter opponent’s strategy Select your mental model to explain opponent’s strategy

8. Modelling Adaptive Behaviour • The management of resource-based, urban systems (like water, energy and transport) can be thought of as higher dimensional (i.e. n-agent) chess games. • When agentsmust adapt to moves of other agents, some learn faster than others, adjusting their strategies so they benefit more from the collective outcomes. This adaptive learning behaviour is reminiscent of “survival of the fittest” in evolutionary biology. • Agent-based modelling(ABM) attempts to cope with such complicated, out-of-equilibrium systems.

9. ABMis actually Simulation • The study of a large number of adaptive agents, with intricate feedback loops between macrostructure and microbehaviour, generally rules out equations-basedmodels. We must trycomputer simulation. • The collective properties of these simulated worlds that a multi-agent approach can help to provide new insights into are those that arise in the dynamics produced by the interactive responses of the agents making up the system. In a truly complex system, some of the collective outcomes may be surprising!

10. CSIRO’s Agent-Based Modelling Working Group (CABM) • CSIRO established a virtual Centre for Complex Systems Science in 2002. • Within this network, researchers in the CABM Working Group undertake agent-based modelling research projects across a broad range of issues  • from deregulating electricity markets to fish and fishing vessel behaviour, • From arid rangelands to saline river catchments.

11. CSIRO’s Agent-Based Modelling Working Group (CABM) • The CABM Working Group nurtures these projects by organizing interaction tasks – e.g. workshops, working group meetings and financial support to sponsor CABM members’ attendance at international conferences. • International experts from Asia, Europe and North America are invited to attend local events. • David Batten is Coordinator of the CABM Working Group and also led the NEMSIM work until late 2005. • Scott Heckbert is Communications Manager and may take over as CABM Coordinator in 2008-09.

12. CSIRO’s Agent-Based Modelling Working Group (CABM) • Several CABM scientists collaborate closely with French scientists belonging to the HEMA (Human Ecosystems Modelling with Agents) network – see Pascal Perez. • Scientists from CSIRO and ANU collaborate directly with others at CIRAD, INRA and CEMAGREF in Montpellier. • HEMA projects make use of the CORMAS (Common-pool Resource management using Multi-Agent Systems) platform developed at CIRAD in Montpellier. • CABM established a technical partnership with Argonne Nat Lab to make use of DIAS, FACET and JeoViewer.

13. CABM Working Group:Recent Activities • Mar 2005 – Workshop (Bourg-Saint Maurice): “Multi-agent Modelling for Environmental Management”[Nils Ferrand] • Dec 2005 – MODSIM Sessions (Melbourne): “Human Ecosystems Modelling and Management with Agents” • Dec 2005 – Symposium (Melbourne): “The Evolution of Diversity” • May 2006 – IT Workshop (Katoomba) “Selection, Self-Organization and Diversity” • Aug 2006 – Workshop (Magnetic Island): “Empirical Agent-based Modelling” [Alex Smajgl] • Aug 2006 – Book published (ANU ePress): “Complex Science for a Complex World: Modelling Human Ecosystems with Agents”[eds: Pascal Perez and David Batten – 14 chapters] • Jun 2007 – Workshop (Perth): “Simulating Human-Agricultural Landscape Interactions with Multi-Agent System Models”[Senthold Asseng] • Nov 2007 – CS Research Summer School (Bathurst): “Agent-based Modelling in Socio-Economic Systems”[Terry Bossomaier]

14. Online version: Free Print-on-demand copy: $49.95 (GST inclusive)

15. Thank You David F Batten Coordinator CSIRO Agent-Based Modelling Working Group (CABM)