The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics.

Reader's guide.- Challenges for machine learning in cooperative information systems.- A modular approach to multi-agent reinforcement learning.- Learning real team solutions.- Learning by linear anticipation in multi-agent systems.- Learning coordinated behavior in a continuous environment.- Multi-agent learning with the success-story algorithm.- On the collaborative object search team: a formulation.- Evolution of coordination as a metaphor for learning in multi-agent systems.- Correlating internal parameters and external performance: Learning Soccer Agents.- Learning agents' reliability through Bayesian Conditioning: A simulation experiment.- A study of organizational learning in multiagents systems.- Cooperative Case-based Reasoning.- Contract-net-based learning in a user-adaptive interface agency.- The communication of inductive inferences.- Addressee Learning and Message Interception for communication load reduction in multiple robot environments.- Learning and communication in Multi-Agent Systems.- Investigating the effects of explicit epistemology on a Distributed learning system.

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