Excerpt on Multi-Agent Planning

Planning is important to an agent because its current and upcoming choices of actions can intentionally establish, or accidentally undo, the conditions that later actions depend upon to reach desirable states of the world. Hence, planning in single-agent systems is concerned with how an agent can efficiently model and select from alternative sequences of actions, preferably without considering every possible sequence. In a multiagent setting, the added complication is that decisions an agent makes about near-term actions can impact the future actions that other agents can (or cannot) take. Similarly, knowing what actions other agents plan to take in the future could impact an agent’s current action choices. And, unlike single agents, multiple agents can act concurrently. Therefore an agent’s choice of action at any given time can impact and be impacted by the action choices of other agents at the same time. Because the space of possible joint courses of action the agents could take grows exponentially with the number of agents (as we will detail later), planning in a multiagent world is inherently intractable, a problem that is compounded in dynamic, partially-observable, and/or non-deterministic environments. Yet, when agents are cooperative, as we will assume in this chapter, then they should strive to make decisions that collectively over time achieve their joint objectives as effectively as possible.

Weiss, Gerhard (2013–03–08). Multiagent Systems (Intelligent Robotics and Autonomous Agents series) (Page 485). The MIT Press. Kindle Edition.

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