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Yazdanpanah, Vahid (author), Gerding, Enrico H. (author), Stein, Sebastian (author), Dastani, Mehdi (author), Jonker, C.M. (author), Norman, Timothy J. (author)
To develop and effectively deploy Trustworthy Autonomous Systems (TAS), we face various social, technological, legal, and ethical challenges in which different notions of responsibility can play a key role. In this work, we elaborate on these challenges, discuss research gaps, and show how the multidimensional notion of responsibility can...
conference paper 2021
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van der Linden, J.G.M. (author), Mulderij, J. (author), Huisman, B. (author), Den Ouden, Joris W. (author), Van Den Akker, Marjan (author), Hoogeveen, Han (author), de Weerdt, M.M. (author)
When trains are finished with their transportation tasks during the day, they are moved to a shunting yard where they are routed, parked, cleaned, subject to regular maintenance checks and repaired during the night. The resulting Train Unit Shunting and Servicing problem motivates advanced research in planning and scheduling in general since...
conference paper 2021
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Mey, A. (author), Oliehoek, F.A. (author)
Machine learning and artificial intelligence models that interact with and in an environment will unavoidably have impact on this environment and change it. This is often a problem as many methods do not anticipate such a change in the environment and thus may start acting sub-optimally. Although efforts are made to deal with this problem, we...
conference paper 2021
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Li, Guangliang (author), Whiteson, Shimon (author), Dibeklioğlu, Hamdi (author), Hung, H.S. (author)
Interactive reinforcement learning provides a way for agents to learn to solve tasks from evaluative feedback provided by a human user. Previous research showed that humans give copious feedback early in training but very sparsely thereafter. In this paper, we investigate the potential of agent learning from trainers’ facial expressions via...
conference paper 2021
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Satsangi, Yash (author), Lim, Sungsu (author), Whiteson, Shimon (author), Oliehoek, F.A. (author), White, Martha (author)
Information gathering in a partially observable environment can be formulated as a reinforcement learning (RL), problem where the reward depends on the agent's uncertainty. For example, the reward can be the negative entropy of the agent's belief over an unknown (or hidden) variable. Typically, the rewards of an RL agent are defined as a...
conference paper 2020
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van der Pol, Elise (author), Kipf, Thomas (author), Oliehoek, F.A. (author), Welling, Max (author)
This work exploits action equivariance for representation learning in reinforcement learning. Equivariance under actions states that transitions in the input space are mirrored by equivalent transitions in latent space, while the map and transition functions should also commute. We introduce a contrastive loss function that enforces action...
conference paper 2020
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Neustroev, G. (author), de Weerdt, M.M. (author)
Reinforcement learning (RL), like any on-line learning method, inevitably faces the exploration-exploitation dilemma. When a learning algorithm requires as few data samples as possible, it is called sample efficient. The design of sample-efficient algorithms is an important area of research. Interestingly, all currently known provably efficient...
conference paper 2020
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Murukannaiah, P.K. (author), Ajmeri, Nirav (author), Jonker, C.M. (author), Singh, M.P. (author)
Ethics is inherently a multiagent concern. However, research on AI ethics today is dominated by work on individual agents: (1) how an autonomous robot or car may harm or (differentially) benefit people in hypothetical situations (the so-called trolley problems) and (2) how a machine learning algorithm may produce biased decisions or...
conference paper 2020
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Renting, B.M. (author), Hoos, Holger H. (author), Jonker, C.M. (author)
Bidding and acceptance strategies have a substantial impact on the outcome of negotiations in scenarios with linear additive and nonlinear utility functions. Over the years, it has become clear that there is no single best strategy for all negotiation settings, yet many fixed strategies are still being developed. We envision a shift in the...
conference paper 2020
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Methenitis, G. (author), Kaisers, Michael (author), la Poutré, J.A. (author)
We study mechanisms to incentivize demand response in smart energy systems. We assume agents that can respond (reduce their demand) with some probability if they prepare prior to the real-ization of the demand. Both preparation and response incur costs to agents. Previous work studies truthful mechanisms that select a minimal set of agents to...
conference paper 2019
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Katt, Sammie (author), Oliehoek, F.A. (author), Amato, Christopher (author)
Model-based Bayesian Reinforcement Learning (BRL) provides a principled solution to dealing with the exploration-exploitation trade-off, but such methods typically assume a fully observable environments. The few Bayesian RL methods that are applicable in partially observable domains, such as the Bayes-Adaptive POMDP (BA-POMDP), scale poorly. To...
conference paper 2019
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Castellini, Jacopo (author), Oliehoek, F.A. (author), Savani, Rahul (author), Whiteson, Shimon (author)
Recent years have seen the application of deep reinforcement learning techniques to cooperative multi-agent systems, with great empirical success. In this work, we empirically investigate the representational power of various network architectures on a series of one-shot games. Despite their simplicity, these games capture many of the crucial...
conference paper 2019
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Tielman, M.L. (author), Jonker, C.M. (author), van Riemsdijk, M.B. (author)
Personal technology such as electronic partners (e-partners) play an increasing role in our daily lives, and can make an important difference by supporting us in various ways. However, when they offer this support, it is important that they do so with an understanding of our choices and what is important to us. To allow an e-partner to...
conference paper 2019
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Koeman, V.J. (author), Hindriks, K.V. (author), Gratch, Jonathan (author), Jonker, C.M. (author)
To improve a negotiator's ability to recognise bidding strategies, we pro-actively provide explanations that are based on the opponent's bids and the negotiator's guesses about the opponent's strategy. We introduce an aberration detection mechanism for recognising strategies and the notion of an explanation matrix. The aberration detection...
conference paper 2019
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de Nijs, F. (author), Theocharous, Georgios (author), Vlassis, Nikos (author), de Weerdt, M.M. (author), Spaan, M.T.J. (author)
Personalized recommendations are increasingly important to engage users and guide them through large systems, for example when recommending points of interest to tourists visiting a popular city. To maximize long-term user experience, the system should consider issuing recommendations sequentially, since by observing the user's response to a...
conference paper 2018
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Jordan Srour, F. (author), Yorke-Smith, N. (author)
The interconnectedness of actors is an antecedent for collective corruption, which in turn can lead to endemic corruption in a society. As a testbed for studying the effects of social interconnectedness on corrupt behaviours, we examine the domain of maritime customs. We add to our existing agent-based simulation a nuanced model of actor...
conference paper 2018
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Picascia, Stefano (author), Termos, Ali (author), Yorke-Smith, N. (author)
The motivation for this extended abstract is to develop an agentbased model (ABM) to capture the existence of migrant and refugee flows, and to explore their effects on urban dynamics. We leverage an extant agent-based model founded on the rent-gap theory, as a lens to study the effect of sizeable refugee migration upon a capital city in West...
conference paper 2018
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de Weerdt, M.M. (author), Albert, Michael (author), Conitzer, Vincent (author), van der Linden, J.G.M. (author)
The problem of optimally scheduling the charging demand of electric vehicles within the constraints of the electricity infrastructure is called the charge scheduling problem. The models of the charging speed, horizon, and charging demand determine the computational complexity of the charge scheduling problem. For about 20 variants the problem is...
conference paper 2018
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Janssen, S.A.M. (author)
We investigate the use of an Agent-based framework to identify and quantify the relationship between security and efficiency within airport terminals. In this framework, we define a novel Security Risk Assessment methodology that explicitly models attacker and defender behavior in a security scenario. It produces a security risk vector,...
conference paper 2017
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Polevoy, G. (author), de Weerdt, M.M. (author), Jonker, C.M. (author)
People often interact repeatedly: with relatives, through file sharing, in politics, etc. Many such interactions are reciprocal: reacting to the actions of the other. In order to facilitate decisions regarding reciprocal interactions, we analyze the development of reciprocation over time. To this end, we propose a model for such interactions...
conference paper 2016
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