foundations of computational agents
The third edition of Artificial Intelligence: foundations of computational agents, Cambridge University Press, 2023 is now available (including full text).
An agent reasoning about what it should do in an environment where it is the only agent is hard enough. However, reasoning about what to do when there are other agents who are also reasoning is much more difficult. An agent in a multiagent setting should reason strategically about other agents; the other agents may act to trick or manipulate the agent or may be available to cooperate with the agent. With multiple agents, it is often optimal to act randomly because other agents can exploit deterministic strategies. Even when the agents are cooperating and have a common goal, the task of coordination and communication makes multiagent reasoning more challenging. However, many domains contain multiple agents and ignoring other agents’ strategic reasoning is not always the best way for an agent to reason.
Taking the point of view of a single agent, the number of agents dimension considers whether the agent explicitly considers other agents:
Single agent reasoning means the agent assumes that there are no other agents in the environment or that all other agents are part of nature, and so are non-purposive. This is a reasonable assumption if there are no other agents or if the other agents are not going to change what they do based on the agent’s action.
Multiple agent reasoning (or multiagent reasoning) means the agent takes the reasoning of other agents into account. This occurs when there are other intelligent agents whose goals or preferences depend, in part, on what the agent does or if the agent must communicate with other agents.
Reasoning in the presence of other agents is much more difficult if the agents can act simultaneously or if the environment is only partially observable. Multiagent systems are considered in Chapter 11.