Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Radulescu, Roxana"'
Addressing the question of how to achieve optimal decision-making under risk and uncertainty is crucial for enhancing the capabilities of artificial agents that collaborate with or support humans. In this work, we address this question in the context
Externí odkaz:
http://arxiv.org/abs/2408.00682
Autor:
Felten, Florian, Ucak, Umut, Azmani, Hicham, Peng, Gao, Röpke, Willem, Baier, Hendrik, Mannion, Patrick, Roijers, Diederik M., Terry, Jordan K., Talbi, El-Ghazali, Danoy, Grégoire, Nowé, Ann, Rădulescu, Roxana
Many challenging tasks such as managing traffic systems, electricity grids, or supply chains involve complex decision-making processes that must balance multiple conflicting objectives and coordinate the actions of various independent decision-makers
Externí odkaz:
http://arxiv.org/abs/2407.16312
Autor:
Röpke, Willem, Reymond, Mathieu, Mannion, Patrick, Roijers, Diederik M., Nowé, Ann, Rădulescu, Roxana
A significant challenge in multi-objective reinforcement learning is obtaining a Pareto front of policies that attain optimal performance under different preferences. We introduce Iterated Pareto Referent Optimisation (IPRO), a principled algorithm t
Externí odkaz:
http://arxiv.org/abs/2402.07182
Autor:
Vamplew, Peter, Foale, Cameron, Hayes, Conor F., Mannion, Patrick, Howley, Enda, Dazeley, Richard, Johnson, Scott, Källström, Johan, Ramos, Gabriel, Rădulescu, Roxana, Röpke, Willem, Roijers, Diederik M.
Research in multi-objective reinforcement learning (MORL) has introduced the utility-based paradigm, which makes use of both environmental rewards and a function that defines the utility derived by the user from those rewards. In this paper we extend
Externí odkaz:
http://arxiv.org/abs/2402.02665
Understanding the emergence of cooperation in systems of computational agents is crucial for the development of effective cooperative AI. Interaction among individuals in real-world settings are often sparse and occur within a broad spectrum of incen
Externí odkaz:
http://arxiv.org/abs/2401.12646
A classic model to study strategic decision making in multi-agent systems is the normal-form game. This model can be generalised to allow for an infinite number of pure strategies leading to continuous games. Multi-objective normal-form games are ano
Externí odkaz:
http://arxiv.org/abs/2301.05755
Autor:
Reymond, Mathieu, Hayes, Conor F., Willem, Lander, Rădulescu, Roxana, Abrams, Steven, Roijers, Diederik M., Howley, Enda, Mannion, Patrick, Hens, Niel, Nowé, Ann, Libin, Pieter
Infectious disease outbreaks can have a disruptive impact on public health and societal processes. As decision making in the context of epidemic mitigation is hard, reinforcement learning provides a methodology to automatically learn prevention strat
Externí odkaz:
http://arxiv.org/abs/2204.05027
We provide an in-depth study of Nash equilibria in multi-objective normal form games (MONFGs), i.e., normal form games with vectorial payoffs. Taking a utility-based approach, we assume that each player's utility can be modelled with a utility functi
Externí odkaz:
http://arxiv.org/abs/2112.06500
Autor:
Vamplew, Peter, Smith, Benjamin J., Kallstrom, Johan, Ramos, Gabriel, Radulescu, Roxana, Roijers, Diederik M., Hayes, Conor F., Heintz, Fredrik, Mannion, Patrick, Libin, Pieter J. K., Dazeley, Richard, Foale, Cameron
The recent paper `"Reward is Enough" by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all intelligence, both natural and artificial. We contest the underlying assumption of Silver et al. tha
Externí odkaz:
http://arxiv.org/abs/2112.15422
We consider preference communication in two-player multi-objective normal-form games. In such games, the payoffs resulting from joint actions are vector-valued. Taking a utility-based approach, we assume there exists a utility function for each playe
Externí odkaz:
http://arxiv.org/abs/2111.09191