Zobrazeno 1 - 10
of 10 650
pro vyhledávání: '"Topcu A"'
In reinforcement learning, conducting task composition by forming cohesive, executable sequences from multiple tasks remains challenging. However, the ability to (de)compose tasks is a linchpin in developing robotic systems capable of learning comple
Externí odkaz:
http://arxiv.org/abs/2408.13376
Negotiation is useful for resolving conflicts in multi-agent systems. We explore autonomous negotiation in a setting where two self-interested rational agents sequentially trade items from a finite set of categories. Each agent has a utility function
Externí odkaz:
http://arxiv.org/abs/2408.11186
Sociotechnical requirements shape the governance of artificially intelligent (AI) systems. In an era where embodied AI technologies are rapidly reshaping various facets of contemporary society, their inherent dynamic adaptability presents a unique bl
Externí odkaz:
http://arxiv.org/abs/2409.00015
Autor:
Galesloot, Maris F. L., Suilen, Marnix, Simão, Thiago D., Carr, Steven, Spaan, Matthijs T. J., Topcu, Ufuk, Jansen, Nils
Robust partially observable Markov decision processes (robust POMDPs) extend classical POMDPs to handle additional uncertainty on the transition and observation probabilities via so-called uncertainty sets. Policies for robust POMDPs must not only be
Externí odkaz:
http://arxiv.org/abs/2408.08770
Recent years have seen increased awareness of the potential significant impacts of computing technologies, both positive and negative. This whitepaper explores how to address possible harmful consequences of computing technologies that might be diffi
Externí odkaz:
http://arxiv.org/abs/2408.06431
Games with incomplete preferences are an important model for studying rational decision-making in scenarios where players face incomplete information about their preferences and must contend with incomparable outcomes. We study the problem of computi
Externí odkaz:
http://arxiv.org/abs/2408.02860
This work proposes a mathematical framework to increase the robustness to rare events of digital twins modelled with graphical models. We incorporate probabilistic model-checking and linear programming into a dynamic Bayesian network to enable the co
Externí odkaz:
http://arxiv.org/abs/2407.20490
Deception is helpful for agents masking their intentions from an observer. We consider a team of agents deceiving their supervisor. The supervisor defines nominal behavior for the agents via reference policies, but the agents share an alternate task
Externí odkaz:
http://arxiv.org/abs/2406.17160
Zero-sum games arise in a wide variety of problems, including robust optimization and adversarial learning. However, algorithms deployed for finding a local Nash equilibrium in these games often converge to non-Nash stationary points. This highlights
Externí odkaz:
http://arxiv.org/abs/2406.03565
Human-Agent Cooperation in Games under Incomplete Information through Natural Language Communication
Developing autonomous agents that can strategize and cooperate with humans under information asymmetry is challenging without effective communication in natural language. We introduce a shared-control game, where two players collectively control a to
Externí odkaz:
http://arxiv.org/abs/2405.14173