AbstractThe article by Shoham, Powers, and Grenager called “If multi-agent learning is the answer, what is the question?” does a great job of laying out the current state of the art and open issues at the intersection of game theory and artificial intelligence (AI). However, from the AI perspective, the term “multiagent learning” applies more broadly than can be usefully framed in game theoretic terms. In this larger context, how (and perhaps whether) multiagent learning can be usefully applied in complex domains is still a large open question
AbstractThis paper surveys recent work on learning in games and delineates the boundary between form...
Shoham et al. identify several important agendas which can help direct research in multi-agent learn...
Multiagent systems (MAS) are distributed systems ofindependent actors, called agents, that cooperate...
AbstractThe area of learning in multi-agent systems is today one of the most fertile grounds for int...
This paper discusses If multi-agent learning is the answer what is the question? [Y. Shoham, R. Powe...
This paper discusses If multi-agent learning is the answer, what is the question? [Y. Shoham, R. Pow...
AbstractThis paper discusses If multi-agent learning is the answer, what is the question? [Y. Shoham...
AbstractI lay out a slight refinement of Shoham et al.'s taxonomy of agendas that I consider sensibl...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Over the past few years, artificial intelligence (AI) has achieved great success in a variety of app...
. In the last years the topic of adaptation and learning in multi-agent systems has gained increasin...
The importance of learning in multi-agent environments as a research and application area is widely ...
The ability to learn is essential to intelligent agents that need to adapt to dynamic, non-determini...
Multiagent systems is an expanding field that blends classical fields like game theory and decentral...
Multiagent systems (MAS) are widely accepted as an important method for solving problems of a distri...
AbstractThis paper surveys recent work on learning in games and delineates the boundary between form...
Shoham et al. identify several important agendas which can help direct research in multi-agent learn...
Multiagent systems (MAS) are distributed systems ofindependent actors, called agents, that cooperate...
AbstractThe area of learning in multi-agent systems is today one of the most fertile grounds for int...
This paper discusses If multi-agent learning is the answer what is the question? [Y. Shoham, R. Powe...
This paper discusses If multi-agent learning is the answer, what is the question? [Y. Shoham, R. Pow...
AbstractThis paper discusses If multi-agent learning is the answer, what is the question? [Y. Shoham...
AbstractI lay out a slight refinement of Shoham et al.'s taxonomy of agendas that I consider sensibl...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Over the past few years, artificial intelligence (AI) has achieved great success in a variety of app...
. In the last years the topic of adaptation and learning in multi-agent systems has gained increasin...
The importance of learning in multi-agent environments as a research and application area is widely ...
The ability to learn is essential to intelligent agents that need to adapt to dynamic, non-determini...
Multiagent systems is an expanding field that blends classical fields like game theory and decentral...
Multiagent systems (MAS) are widely accepted as an important method for solving problems of a distri...
AbstractThis paper surveys recent work on learning in games and delineates the boundary between form...
Shoham et al. identify several important agendas which can help direct research in multi-agent learn...
Multiagent systems (MAS) are distributed systems ofindependent actors, called agents, that cooperate...