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A Study of Computational and Human Strategies in Revelation Games
, 2011
"... Revelation games are bilateral bargaining games in which agents may choose to truthfully reveal their private information before engaging in multiple rounds of negotiation. They are analogous to realworld situations in which people need to decide whether to disclose information such as medical reco ..."
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Cited by 16 (9 self)
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Revelation games are bilateral bargaining games in which agents may choose to truthfully reveal their private information before engaging in multiple rounds of negotiation. They are analogous to realworld situations in which people need to decide whether to disclose information such as medical records or university transcripts when negotiating over health plans and business transactions. This paper presents an agentdesign that is able to negotiate proficiently with people in a revelation game with different dependencies that hold between players. The agent modeled the social factors that affect the players ’ revelation decisions on people’s negotiation behavior. It was empirically shown to outperform people in empirical evaluations as well as agents playing equilibrium strategies. It was also more likely to reach agreement than people or equilibrium agents.
Finding Optimal Abstract Strategies in ExtensiveForm Games
"... Extensiveform games are a powerful model for representing interactions between agents. Nash equilibrium strategies are a common solution concept for extensiveform games and, in twoplayer zerosum games, there are efficient algorithms for calculating such strategies. In large games, this computati ..."
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Cited by 12 (7 self)
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Extensiveform games are a powerful model for representing interactions between agents. Nash equilibrium strategies are a common solution concept for extensiveform games and, in twoplayer zerosum games, there are efficient algorithms for calculating such strategies. In large games, this computation may require too much memory and time to be tractable. A standard approach in such cases is to apply a lossy statespace abstraction technique to produce a smaller abstract game that game equilibrium is close to an equilibrium strategy in the unabstracted game. Recent work has shown that this assumption is unreliable, and an arbitrary Nash equilibrium in the abstract game is unlikely to be even near the least suboptimal strategy that can be represented in that space. In this work, we present for the first time an algorithm which efficiently finds optimal abstract strategies — strategies with minimal exploitability in the unabstracted game. We use this technique to find the least exploitable strategy ever reported for twoplayer limit Texas hold’em.
Nonmanipulable Selections from a Tournament
 In Proceedings of 21st Intl. Joint Conf. on Artificial Intelligence 2009 (To Appear
"... A tournament is a binary dominance relation on a set of alternatives. Tournaments arise in many contexts that are relevant to AI, most notably in voting (as a method to aggregate the preferences of agents). There are many works that deal with choice rules that select a desirable alternative from a t ..."
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Cited by 4 (2 self)
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A tournament is a binary dominance relation on a set of alternatives. Tournaments arise in many contexts that are relevant to AI, most notably in voting (as a method to aggregate the preferences of agents). There are many works that deal with choice rules that select a desirable alternative from a tournament, but very few of them deal directly with incentive issues, despite the fact that gametheoretic considerations are crucial with respect to systems populated by selfish agents. We deal with the problem of the manipulation of choice rules by considering two types of manipulation. We say that a choice rule is monotonic if an alternative cannot get itself selected by losing on purpose, and pairwise nonmanipulable if a pair of alternatives cannot make one of them the winner by reversing the outcome of the match between them. Our main result is a combinatorial construction of a choice rule that is monotonic, pairwise nonmanipulable, and onto the set of alternatives, for any number of alternatives besides three. 1
Theory, Economics
"... argumentation frameworks have received increasing interest in artificial intelligence as a convenient model for reasoning about general characteristics of argument. Such a framework consists of a set of arguments and a binary defeat relation among them. Various semantic and computational approaches ..."
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argumentation frameworks have received increasing interest in artificial intelligence as a convenient model for reasoning about general characteristics of argument. Such a framework consists of a set of arguments and a binary defeat relation among them. Various semantic and computational approaches have been developed to characterise the acceptability of individual arguments in a given argumentation framework. However, little work exists on understanding the strategic aspects of abstract argumentation among selfinterested agents. In this paper, we introduce (gametheoretic) argumentation mechanism design (ArgMD), which enables the design and analysis of argumentation mechanisms for selfinterested agents. We define the notion of a directrevelation argumentation mechanism, in which agents must decide which arguments to reveal simultaneously. We then design a particular direct argumentation mechanism and prove that it is strategy proof under specific conditions; that is, the strategy profile in which each agent reveals its arguments truthfully is a dominant strategy equilibrium.
Chapter 16 Argumentation and Game Theory
"... In a large class of multiagent systems, agents are selfinterested in the sense that each agent is interested only in furthering its individual goals, which may or may not coincide with others ’ goals. When such agents engage in argument, they would be expected to argue strategically in such a way ..."
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In a large class of multiagent systems, agents are selfinterested in the sense that each agent is interested only in furthering its individual goals, which may or may not coincide with others ’ goals. When such agents engage in argument, they would be expected to argue strategically in such a way that makes it more likely for their argumentative goals to be achieved. What we mean by arguing strategically is that instead of making arbitrary arguments, an agent would carefully choose its argumentative moves in order to further its own objectives. The mathematical study of strategic interaction is Game Theory, which was pioneered by von Neuman and Morgenstern [13]. A setting of strategic interaction is modelled as a game, which consists of a set of players, a set of actions available to them, and a rule that determines the outcome given players ’ chosen actions. In an argumentation scenario, the set of actions are typically the set of argumentative moves (e.g. asserting a claim or challenging a claim), and the outcome rule is the criterion by which arguments are evaluated (e.g. a judge’s attitude or a social norm). Generally, game theory can be used to achieve two goals: 1. undertake precise analysis of interaction in particular strategic settings, with a view to predicting the outcome; 2. design rules of the game in such a way that selfinterested agents behave in some desirable manner (e.g. tell the truth); this is called mechanism design; Both these approaches are quite useful for the study of argumentation in multiagent systems. On one hand, an agent may use game theory to analyse a given argumentative situation in order to choose the best strategy. On the other hand, we
I the Dynamics of Argumentation
, 2015
"... 2 Main task: formal verification of infinitestate Dynamic Argumentation Systems (DAS) I model checking is appropriate for controlintensive applications......but less suited for dataintensive applications (data typically range over infinite domains) [1] 3 Key contributions: I DAS: a formal model f ..."
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2 Main task: formal verification of infinitestate Dynamic Argumentation Systems (DAS) I model checking is appropriate for controlintensive applications......but less suited for dataintensive applications (data typically range over infinite domains) [1] 3 Key contributions: I DAS: a formal model for the dynamics of argumentation I FOATL: a specification language for DAS I truth preserving static and dynamic bisimulations 2 Outline
Formal Analysis of Dialogues on Infinite Argumentation Frameworks
"... The paper analyses multiagent strategic dialogues on possibly infinite argumentation frameworks. We develop a formal model for representing such dialogues, and introduce FOAATL, a firstorder extension of alternatingtime logic, for expressing the interplay of strategic and argumentationtheoret ..."
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The paper analyses multiagent strategic dialogues on possibly infinite argumentation frameworks. We develop a formal model for representing such dialogues, and introduce FOAATL, a firstorder extension of alternatingtime logic, for expressing the interplay of strategic and argumentationtheoretic properties. This setting is investigated with respect to the model checking problem, by means of a suitable notion of bisimulation. This notion of bisimulation is also used to shed light on how static properties of argumentation frameworks influence their dynamic behaviour. 1
Proceedings of the TwentyThird International Joint Conference on Artificial Intelligence AudienceBased Uncertainty in Abstract Argument Games
"... The paper generalizes abstract argument games to cope with cases where proponent and opponent argue in front of an audience whose type is known only with uncertainty. The generalization, which makes use of basic tools from probability theory, is motivated by several examples and delivers a class of ..."
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The paper generalizes abstract argument games to cope with cases where proponent and opponent argue in front of an audience whose type is known only with uncertainty. The generalization, which makes use of basic tools from probability theory, is motivated by several examples and delivers a class of abstract argument games whose adequacy is proven robust against uncertainty. 1