An Evolutionary Approach to Balancing Deliberation and Reactiveness in a Multi-Agent Scenario

スポンサーリンク

概要

• 論文の詳細を見る

• Regarding planning behavior in an ecosystem a tradeoff between cost and time exists. If an agent has to plan he will tend to minimize the costs of the plan execution which will lead him to longer deliberation in order to find a suitable low cost plan. On the other hand the agent is situated in a competitive environment which gives him the highest guarantee of plan execution if his planning behavior is strongly reactive. Thus, a dilemma-like situation emerges which is due to the bounded rationality [1] which characterizes living beings as well as intelligent agents in complex environments : optimizing its outcome with its limited abilities. Evolution can be a source for diversity and complexity, but also for stability in a dynamical system such as system of multiple, goal-driven agents which have to do planning in an ever changing dynamic environment in order to fulfill their goals. We assume such agents to be selfishly motivated in the first place and to compete for resources. Executing a plan is connected with costs, e. g. energy consumed when moving a robot. Fulfilling a goal gives a payoff to an agent, e. g. reaching a loading-station for a robot. Regarding agents as dissipative systems makes it even costly to take no actions. Agents which reason deliberately can reduce arising costs by choosing a carefully selected low-cost plan. On the other hand, such committing agents might be confronted with a changed environmental situation when executing their plan after time-consuming deliberation in a dynamic environment. This might result in failure of execution. Reactive agents will not spend much time on reasoning but will execute the fastest plan, which is normally not the cheapest, in order to fulfill their goal. Because reactive agents do not spend much or no time on planning they are likely to fulfill most of their goal as long as these goals are within their cost range. In this paper we model this tradeoff problem and will show some simulation results.

• 一般社団法人情報処理学会の論文
• 1996-03-06

著者

• Tani Jun

  Sony Computer Science Laboratory Inc.

• Baczewski Joachim

  Department Of Administration Engineering Faculty Of Science And Technology Keio University

関連論文

• Evolving Planning Behaviors in an Artificial Ecosystem
• An Evolutionary Approach to Balancing Deliberation and Reactiveness in a Multi-Agent Scenario
• Planning in an Artificial Ecosystem
• Self-organizing Internal Representation in Learning of Navigation: A Physical Experiment by the Mobile Robot YAMABICO
• Embedding Symbolic Process into Deterministic Chaos

スポンサーリンク