Zobrazeno 1 - 10
of 219
pro vyhledávání: '"Everett, Richard A."'
Autor:
Madhushani, Udari, McKee, Kevin R., Agapiou, John P., Leibo, Joel Z., Everett, Richard, Anthony, Thomas, Hughes, Edward, Tuyls, Karl, Duéñez-Guzmán, Edgar A.
In social psychology, Social Value Orientation (SVO) describes an individual's propensity to allocate resources between themself and others. In reinforcement learning, SVO has been instantiated as an intrinsic motivation that remaps an agent's reward
Externí odkaz:
http://arxiv.org/abs/2305.00768
Autor:
Gemp, Ian, Anthony, Thomas, Bachrach, Yoram, Bhoopchand, Avishkar, Bullard, Kalesha, Connor, Jerome, Dasagi, Vibhavari, De Vylder, Bart, Duenez-Guzman, Edgar, Elie, Romuald, Everett, Richard, Hennes, Daniel, Hughes, Edward, Khan, Mina, Lanctot, Marc, Larson, Kate, Lever, Guy, Liu, Siqi, Marris, Luke, McKee, Kevin R., Muller, Paul, Perolat, Julien, Strub, Florian, Tacchetti, Andrea, Tarassov, Eugene, Wang, Zhe, Tuyls, Karl
The Game Theory & Multi-Agent team at DeepMind studies several aspects of multi-agent learning ranging from computing approximations to fundamental concepts in game theory to simulating social dilemmas in rich spatial environments and training 3-d hu
Externí odkaz:
http://arxiv.org/abs/2209.10958
Large graphs commonly appear in social networks, knowledge graphs, recommender systems, life sciences, and decision making problems. Summarizing large graphs by their high level properties is helpful in solving problems in these settings. In spectral
Externí odkaz:
http://arxiv.org/abs/2207.14589
Autor:
Cultural General Intelligence Team, Bhoopchand, Avishkar, Brownfield, Bethanie, Collister, Adrian, Lago, Agustin Dal, Edwards, Ashley, Everett, Richard, Frechette, Alexandre, Oliveira, Yanko Gitahy, Hughes, Edward, Mathewson, Kory W., Mendolicchio, Piermaria, Pawar, Julia, Pislar, Miruna, Platonov, Alex, Senter, Evan, Singh, Sukhdeep, Zacherl, Alexander, Zhang, Lei M.
Cultural transmission is the domain-general social skill that allows agents to acquire and use information from each other in real-time with high fidelity and recall. In humans, it is the inheritance process that powers cumulative cultural evolution,
Externí odkaz:
http://arxiv.org/abs/2203.00715
Autor:
Kopparapu, Kavya, Duéñez-Guzmán, Edgar A., Matyas, Jayd, Vezhnevets, Alexander Sasha, Agapiou, John P., McKee, Kevin R., Everett, Richard, Marecki, Janusz, Leibo, Joel Z., Graepel, Thore
A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to cooperate. This is particularly critical in situations when other agents have hidden, possibly misa
Externí odkaz:
http://arxiv.org/abs/2201.01816
Collaborating with humans requires rapidly adapting to their individual strengths, weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement learning techniques, such as self-play (SP) or population play (PP), produce agents
Externí odkaz:
http://arxiv.org/abs/2110.08176
Autor:
Gemp, Ian, Savani, Rahul, Lanctot, Marc, Bachrach, Yoram, Anthony, Thomas, Everett, Richard, Tacchetti, Andrea, Eccles, Tom, Kramár, János
Nash equilibrium is a central concept in game theory. Several Nash solvers exist, yet none scale to normal-form games with many actions and many players, especially those with payoff tensors too big to be stored in memory. In this work, we propose an
Externí odkaz:
http://arxiv.org/abs/2106.01285
Generalization is a major challenge for multi-agent reinforcement learning. How well does an agent perform when placed in novel environments and in interactions with new co-players? In this paper, we investigate and quantify the relationship between
Externí odkaz:
http://arxiv.org/abs/2102.08370
Autor:
Bakker, Michiel A., Everett, Richard, Weidinger, Laura, Gabriel, Iason, Isaac, William S., Leibo, Joel Z., Hughes, Edward
The real world is awash with multi-agent problems that require collective action by self-interested agents, from the routing of packets across a computer network to the management of irrigation systems. Such systems have local incentives for individu
Externí odkaz:
http://arxiv.org/abs/2102.06911
Autor:
Bachrach, Yoram, Everett, Richard, Hughes, Edward, Lazaridou, Angeliki, Leibo, Joel Z., Lanctot, Marc, Johanson, Michael, Czarnecki, Wojciech M., Graepel, Thore
Publikováno v:
Artificial Intelligence 288 (2020): 103356
When autonomous agents interact in the same environment, they must often cooperate to achieve their goals. One way for agents to cooperate effectively is to form a team, make a binding agreement on a joint plan, and execute it. However, when agents a
Externí odkaz:
http://arxiv.org/abs/2010.10380