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Collective Argumentation: The Case of Aggregating Support-Relations of Bipolar Argumentation Frameworks 集体论证:双极性论证框架的聚合支持关系
Pub Date : 2021-06-22 DOI: 10.4204/EPTCS.335.8
Weiwei Chen
In many real-life situations that involve exchanges of arguments, individuals may differ on their assessment of which supports between the arguments are in fact justified, i.e., they put forward different support-relations. When confronted with such situations, we may wish to aggregate individuals’ argumentation views on support-relations into a collective view, which is acceptable to the group. In this paper, we assume that under bipolar argumentation frameworks, individuals are equipped with a set of arguments and a set of attacks between arguments, but with possibly different supportrelations. Using the methodology in social choice theory, we analyze what semantic properties of bipolar argumentation frameworks can be preserved by aggregation rules during the aggregation of support-relations.
在许多现实生活中涉及到争论的情况下,个体对于争论中哪一种支持是正确的评估可能会有所不同,也就是说,他们提出了不同的支持关系。当面对这种情况时,我们可能希望将个人对支持关系的论证观点汇总为集体观点,这是群体可以接受的。在本文中,我们假设在双极性论证框架下,个体具有一组论证和一组论证之间的攻击,但可能具有不同的支持关系。运用社会选择理论的方法,分析了在支持关系聚合过程中,聚合规则可以保留双极论证框架的哪些语义属性。
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引用次数: 0
Communication Pattern Models: An Extension of Action Models for Dynamic-Network Distributed Systems 通信模式模型:动态网络分布式系统动作模型的扩展
Pub Date : 2021-06-22 DOI: 10.4204/EPTCS.335.29
Diego A. Vel'azquez, Armando Castañeda, D. Rosenblueth
Halpern and Moses were the first to recognize, in 1984, the importance of a formal treatment of knowledge in distributed computing. Many works in distributed computing, however, still employ informal notions of knowledge. Hence, it is critical to further study such formalizations. Action models, a significant approach to modeling dynamic epistemic logic, have only recently been applied to distributed computing, for instance, by Goubault, Ledent, and Rajsbaum. Using action models for analyzing distributed-computing environments, as proposed by these authors, has drawbacks, however. In particular, a direct use of action models may cause such models to grow exponentially as the computation of the distributed system evolves. Hence, our motivation is finding compact action models for distributed systems. We introduce communication pattern models as an extension of both ordinary action models and their update operator. We give a systematic construction of communication pattern models for a large variety of distributed-computing models called dynamic-network models. For a proper subclass of dynamic-network models called oblivious, the communication pattern model remains the same throughout the computation.
1984年,Halpern和Moses首先认识到在分布式计算中对知识进行正式处理的重要性。然而,分布式计算中的许多工作仍然使用非正式的知识概念。因此,进一步研究这种形式化是至关重要的。动作模型是建模动态认知逻辑的一种重要方法,直到最近才被应用到分布式计算中,例如Goubault、Ledent和Rajsbaum。然而,正如这些作者所建议的那样,使用动作模型来分析分布式计算环境有缺点。特别是,直接使用动作模型可能会导致这些模型随着分布式系统计算的发展而呈指数级增长。因此,我们的动机是为分布式系统寻找紧凑的操作模型。我们引入通信模式模型作为普通动作模型及其更新操作符的扩展。本文系统地构建了各种分布式计算模型——动态网络模型的通信模式模型。对于动态网络模型的一个适当子类——遗忘模型,通信模式模型在整个计算过程中保持不变。
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引用次数: 7
Game-theoretic Models of Moral and Other-Regarding Agents 道德和他者行为的博弈论模型
Pub Date : 2020-12-17 DOI: 10.4204/EPTCS.335.19
Gabriel Istrate
We investigate Kantian equilibria in finite normal form games, a class of non-Nashian, morally motivated courses of action that was recently proposed in the economics literature. We highlight a number of problems with such equilibria, including computational intractability, a high price of miscoordination, and expensive/problematic extension to general normal form games. We point out that such a proper generalization will likely involve the concept of program equilibrium. Finally we propose some general, intuitive, computationally tractable, other-regarding equilibria related to Kantian equilibria, as well as a class of courses of action that interpolates between purely self-regarding and Kantian behavior.
我们研究了有限范式博弈中的康德均衡,这是最近在经济学文献中提出的一类非纳什式的、道德动机的行为。我们强调了这种均衡的一些问题,包括计算难解性,高代价的不协调,以及昂贵的/有问题的扩展到一般的范式博弈。我们指出,这种适当的推广可能涉及到程序平衡的概念。最后,我们提出了一些与康德均衡相关的一般的、直观的、计算上可处理的、与他人相关的均衡,以及一类介于纯粹自我关注和康德行为之间的行动过程。
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引用次数: 2
Strategic Voting Under Uncertainty About the Voting Method 投票方式不确定性下的策略性投票
Pub Date : 2019-07-19 DOI: 10.4204/EPTCS.297.17
W. Holliday, E. Pacuit
Much of the theoretical work on strategic voting makes strong assumptions about what voters know about the voting situation. A strategizing voter is typically assumed to know how other voters will vote and to know the rules of the voting method. A growing body of literature explores strategic voting when there is uncertainty about how others will vote. In this paper, we study strategic voting when there is uncertainty about the voting method. We introduce three notions of manipulability for a set of voting methods: sure, safe, and expected manipulability. With the help of a computer program, we identify voting scenarios in which uncertainty about the voting method may reduce or even eliminate a voter's incentive to misrepresent her preferences. Thus, it may be in the interest of an election designer who wishes to reduce strategic voting to leave voters uncertain about which of several reasonable voting methods will be used to determine the winners of an election.
许多关于策略性投票的理论工作都对选民对投票情况的了解程度做出了强有力的假设。制定策略的选民通常被认为知道其他选民将如何投票,并知道投票方法的规则。越来越多的文献在不确定其他人会如何投票的情况下探讨策略性投票。本文研究了投票方式存在不确定性时的策略性投票。我们为一组投票方法引入了可操控性的三个概念:确定性、安全性和预期可操控性。在计算机程序的帮助下,我们识别投票场景,其中投票方法的不确定性可能会减少甚至消除选民歪曲其偏好的动机。因此,选举设计者希望减少策略性投票,让选民不确定将使用几种合理的投票方法中的哪一种来决定选举的获胜者,这可能符合他们的利益。
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引用次数: 1
Aggregating Probabilistic Judgments 聚合概率判断
Pub Date : 2019-07-19 DOI: 10.4204/EPTCS.297.18
Magdalena Ivanovska, M. Slavkovik
In this paper we explore the application of methods for classical judgment aggregation in pooling probabilistic opinions on logically related issues. For this reason, we first modify the Boolean judgment aggregation framework in the way that allows handling probabilistic judgments and then define probabilistic aggregation functions obtained by generalization of the classical ones. In addition, we discuss essential desirable properties for the aggregation functions and explore impossibility results.
本文探讨了经典判断聚合方法在逻辑相关问题的概率意见汇集中的应用。为此,我们首先对布尔判断聚合框架进行修改,使其能够处理概率判断,然后定义由经典判断泛化得到的概率聚合函数。此外,我们还讨论了聚集函数的基本理想性质,并探讨了不可能结果。
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引用次数: 1
Learning Probabilities: Towards a Logic of Statistical Learning 学习概率:迈向统计学习的逻辑
Pub Date : 2019-07-19 DOI: 10.4204/EPTCS.297.3
A. Baltag, S. R. Rad, S. Smets
We propose a new model for forming beliefs and learning about unknown probabilities (such as the probability of picking a red marble from a bag with an unknown distribution of coloured marbles). The most widespread model for such situations of 'radical uncertainty' is in terms of imprecise probabilities, i.e. representing the agent's knowledge as a set of probability measures. We add to this model a plausibility map, associating to each measure a plausibility number, as a way to go beyond what is known with certainty and represent the agent's beliefs about probability. There are a number of standard examples: Shannon Entropy, Centre of Mass etc. We then consider learning of two types of information: (1) learning by repeated sampling from the unknown distribution (e.g. picking marbles from the bag); and (2) learning higher-order information about the distribution (in the shape of linear inequalities, e.g. we are told there are more red marbles than green marbles). The first changes only the plausibility map (via a 'plausibilistic' version of Bayes' Rule), but leaves the given set of measures unchanged; the second shrinks the set of measures, without changing their plausibility. Beliefs are defined as in Belief Revision Theory, in terms of truth in the most plausible worlds. But our belief change does not comply with standard AGM axioms, since the revision induced by (1) is of a non-AGM type. This is essential, as it allows our agents to learn the true probability: we prove that the beliefs obtained by repeated sampling converge almost surely to the correct belief (in the true probability). We end by sketching the contours of a dynamic doxastic logic for statistical learning.
我们提出了一种新的模型,用于形成信念和学习未知概率(例如从彩色弹珠分布未知的袋子中取出红色弹珠的概率)。对于这种“根本不确定性”的情况,最广泛的模型是不精确概率,即将代理的知识表示为一组概率度量。我们在这个模型中添加了一个似是而非的图,将每个度量关联到一个似是而非的数字,作为一种超越已知确定性的方式,并代表代理对概率的信念。有许多标准的例子:香农熵、质心等。然后我们考虑学习两种类型的信息:(1)通过从未知分布中重复采样来学习(例如从袋子中取出弹珠);(2)学习关于分布的高阶信息(以线性不等式的形式,例如,我们被告知红色弹珠比绿色弹珠多)。第一种方法只改变可信性图(通过贝叶斯规则的“可信性”版本),但不改变给定的度量集;第二种方法在不改变其合理性的前提下缩减了一系列措施。信念在信念修正理论中被定义为,在最似是而非的世界里的真理。但是我们的信念改变不符合标准的AGM公理,因为(1)引起的修正是非AGM类型的。这是必不可少的,因为它允许我们的代理学习真实概率:我们证明通过重复采样获得的信念几乎肯定会收敛到正确的信念(在真实概率中)。最后,我们勾画出统计学习的动态动态逻辑的轮廓。
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引用次数: 1
Causality and Epistemic Reasoning in Byzantine Multi-Agent Systems 拜占庭多智能体系统中的因果关系和认知推理
Pub Date : 2019-07-19 DOI: 10.4204/EPTCS.297.19
R. Kuznets, Laurent Prosperi, U. Schmid, Krisztina Fruzsa
Causality is an important concept both for proving impossibility results and for synthesizing efficient protocols in distributed computing. For asynchronous agents communicating over unreliable channels, causality is well studied and understood. This understanding, however, relies heavily on the assumption that agents themselves are correct and reliable. We provide the first epistemic analysis of causality in the presence of byzantine agents, i.e., agents that can deviate from their protocol and, thus, cannot be relied upon. Using our new framework for epistemic reasoning in fault-tolerant multi-agent systems, we determine the byzantine analog of the causal cone and describe a communication structure, which we call a multipede, necessary for verifying preconditions for actions in this setting.
在分布式计算中,因果关系是证明不可能结果和综合有效协议的重要概念。对于通过不可靠通道进行通信的异步代理,因果关系得到了很好的研究和理解。然而,这种理解在很大程度上依赖于代理本身是正确和可靠的假设。我们提供了在拜占庭代理的存在下的第一个因果关系的认知分析,即,代理可以偏离他们的协议,因此,不能依赖。使用我们在容错多智能体系统中新的认知推理框架,我们确定了因果锥体的拜占庭模拟,并描述了一种通信结构,我们称之为multipede,这是验证这种设置中行动的先决条件所必需的。
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引用次数: 5
Uncertainty About Evidence 证据的不确定性
Pub Date : 2019-07-19 DOI: 10.4204/EPTCS.297.5
Adam Bjorndahl, Aybüke Özgün
We develop a logical framework for reasoning about knowledge and evidence in which the agent may be uncertain about how to interpret their evidence. Rather than representing an evidential state as a fixed subset of the state space, our models allow the set of possible worlds that a piece of evidence corresponds to to vary from one possible world to another, and therefore itself be the subject of uncertainty. Such structures can be viewed as (epistemically motivated) generalizations of topological spaces. In this context, there arises a natural distinction between what is actually entailed by the evidence and what the agent knows is entailed by the evidence -- with the latter, in general, being much weaker. We provide a sound and complete axiomatization of the corresponding bi-modal logic of knowledge and evidence entailment, and investigate some natural extensions of this core system, including the addition of a belief modality and its interaction with evidence interpretation and entailment, and the addition of a "knowability" modality interpreted via a (generalized) interior operator.
我们开发了一个逻辑框架来推理知识和证据,在这个框架中,代理人可能不确定如何解释他们的证据。我们的模型不是将证据状态表示为状态空间的一个固定子集,而是允许证据对应的一组可能世界从一个可能世界变化到另一个可能世界,因此本身就是不确定性的主题。这样的结构可以被看作是拓扑空间的一般化。在这种情况下,证据所包含的实际内容与行为人所知道的证据所包含的内容之间产生了自然的区别,后者通常要弱得多。我们提供了相应的知识和证据蕴涵的双模态逻辑的健全和完整的公理化,并研究了该核心系统的一些自然扩展,包括增加信念模态及其与证据解释和蕴涵的相互作用,以及增加通过(广义)内部算子解释的“可知性”模态。
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引用次数: 5
Measuring Belief and Risk Attitude 测量信念和风险态度
Pub Date : 2019-07-19 DOI: 10.4204/EPTCS.297.22
Sven Neth
Ramsey (1926) sketches a proposal for measuring the subjective probabilities of an agent by their observable preferences, assuming that the agent is an expected utility maximizer. I show how to extend the spirit of Ramsey's method to a strictly wider class of agents: risk-weighted expected utility maximizers (Buchak 2013). In particular, I show how we can measure the risk attitudes of an agent by their observable preferences, assuming that the agent is a risk-weighted expected utility maximizer. Further, we can leverage this method to measure the subjective probabilities of a risk-weighted expected utility maximizer.
拉姆齐(1926)提出了一个建议,假设代理人是预期效用最大化者,通过可观察到的偏好来衡量代理人的主观概率。我展示了如何将拉姆齐方法的精神扩展到更广泛的代理人类别:风险加权预期效用最大化者(Buchak 2013)。特别是,我展示了我们如何通过可观察到的偏好来衡量代理人的风险态度,假设代理人是风险加权期望效用最大化者。此外,我们可以利用这种方法来度量风险加权期望效用最大化者的主观概率。
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引用次数: 1
A Conceptually Well-Founded Characterization of Iterated Admissibility Using an "All I Know" Operator 利用“全部我知道”算子对迭代可容许性的概念上有充分根据的刻画
Pub Date : 2019-07-19 DOI: 10.4204/EPTCS.297.15
Joseph Y. Halpern, R. Pass
Brandenburger, Friedenberg, and Keisler provide an epistemic characterization of iterated admissibility (IA), also known as iterated deletion of weakly dominated strategies, where uncertainty is represented using LPSs (lexicographic probability sequences). Their characterization holds in a rich structure called a complete structure, where all types are possible. In earlier work, we gave a characterization of iterated admissibility using an "all I know" operator, that captures the intuition that "all the agent knows" is that agents satisfy the appropriate rationality assumptions. That characterization did not need complete structures and used probability structures, not LPSs. However, that characterization did not deal with Samuelson's conceptual concern regarding IA, namely, that at higher levels, players do not consider possible strategies that were used to justify their choice of strategy at lower levels. In this paper, we give a characterization of IA using the all I know operator that does deal with Samuelson's concern. However, it uses LPSs. We then show how to modify the characterization using notions of "approximate belief" and "approximately all I know" so as to deal with Samuelson's concern while still working with probability structures.
Brandenburger, Friedenberg和Keisler提供了迭代可接受性(IA)的认识论表征,也称为弱优势策略的迭代删除,其中不确定性使用LPSs(词典概率序列)表示。它们的特征体现在一个被称为完整结构的丰富结构中,在这个结构中,所有类型都是可能的。在早期的工作中,我们使用“所有我知道的”算子给出了迭代可接受性的表征,该算子捕获了“所有代理知道的”的直觉,即代理满足适当的合理性假设。这种描述不需要完整的结构,而是使用概率结构,而不是lps。然而,这种描述并没有处理Samuelson关于IA的概念性担忧,即在较高的关卡中,玩家不会考虑可能的策略来证明他们在较低关卡中所选择的策略是正确的。在本文中,我们使用所有我知道的算子给出了IA的一个表征,它确实处理了Samuelson的问题。然而,它使用的是LPSs。然后,我们展示了如何使用“近似信念”和“近似我所知道的一切”的概念来修改表征,以便在处理萨缪尔森的问题时仍然使用概率结构。
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引用次数: 1
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Theoretical Aspects of Rationality and Knowledge
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