Data-Informed Knowledge and Strategies (Extended Abstract)

The paper studies strategic abilities that rise from restrictions on the information sharing in multi-agent systems. The main technical result is a sound and complete logical system that describes the interplay between the knowledge and the strategic ability modalities.

This paper presents a sound and complete logical system whose atomic sentences are the equalities of recursive terms involving sets. There are two interpretations of this language: one makes use of non-wellfounded sets with finite transitive closure, and the other uses pointed finite graphs modulo bisimulation. Our logical system is a sequent-style deduction system. The main axioms and inference rules come from the $\mbox{{\it FLR}$_0$}$ -proof system from [6], including the Recursion Inference Rule (but an additional axiom is needed), and also axioms corresponding to the extensionality axiom of set theory.

Multi-agent systems defined on a network can be used for modelling the competition between companies in terms of market dominance. In view of the enormous size of the search space for winning strategies of initial configuration of resource allocation on network, we focus our search on the subspace defined by special local clustering effects, using the recently developed evolutionary computational algorithm. Strategies that emphasize local solidarity, measured by the formation of clusters in the form of triangles linkage between members of the same company, prove to be effective in winning both the market share with high probability and high speed. The result provides a good guideline to improve the collective competitiveness in a network of agents. The formulation is based on the Ising model in statistical physics and the evolutionary game is based on Monte Carlo simulation. Significance and the application of the algorithm in the context of econophysics and damage spreading in network are discussed.

Electric vehicles and hybrid vehicles have become one of the relevant and sustainable solutions for the transportation of tomorrow. They are the most presenting and studying by the research; seen their advantages in terms of composition and movement. Within this type of vehicles, energy management is a fundamental tool to ensure smooth operation during the rolling cycle, while optimizing available energy sources and even predicting future power demand. This paper proposes a method of optimization and prediction of energy based on the Markov chains. The work requires the development of a suitable system to control the electric model of powertrain: the Electric motor and the Hybrid Electric Source (HES). The given studied vehicle has a HES to processing in real-time. It is, therefore, interesting to define a flexible and fast management system, which can process the available sub-components. We use, therefore, a multi-agent system (MAS) to intelligently manage the available energy in a Fuel Cell (FC) and Super-capacitor (SC). During the simulation stage, we seek to apply an online prediction and see how the system reacts in terms of optimized power. Comparing also the results found by the adopted method to others of the same case studied. This allowing well define the most efficient and suitable laws of management for an HEV.

The paper investigates the second-order blameworthiness or duty to warn modality "one coalition knew how another coalition could have prevented an outcome''. The main technical result is a sound and complete logical system that describes the interplay between the distributed knowledge and the duty to warn modalities.

If an agent, or a coalition of agents, has a strategy, knows that she has a strategy, and knows what the strategy is, then she has a know-how strategy. Several modal logics of coalition power for know-how strategies have been studied before.
 The contribution of the article is three-fold. First, it proposes a new class of know-how strategies that depend on the intelligence information about the opponents’ actions. Second, it shows that the coalition power modality for the proposed new class of strategies cannot be expressed through the standard know-how modality. Third, it gives a sound and complete logical system that describes the interplay between the coalition power modality with intelligence and the distributed knowledge modality in games with imperfect information.

The author introduces a temporal logic called interval division logic, IDL, based on the constructive temporal ontology. In IDL, time is regarded as a constructive object which is built from an interval by iterating the interval division every time a new temporal fact is recognized. IDL as a sound and complete logical system which is as expressive as the Buich tree automata. In order to examine how the persistence problem is treated on this ontology, the author extends a nonmonotonic version of IDL based on the model preference in which any belief is changed as late as possible in the epistemological order rather than the temporal order. The Yale shooting problem is discussed in this framework.

Experimental analysis of agent strategies in multiagent systems presents a tradeoff between granularity and statistical confidence. Collecting a large amount of data about each strategy profile improves confidence, but restricts the range of strategies and profiles that can be explored. We propose a flexible approach, where multiple game-theoretic formulations can be constructed to model the same underlying scenario (observation dataset). The prospect of incorrectly selecting an empirical model is termed generalization risk, and the generalization risk framework we describe provides a general criterion for empirical modeling choices, such as adoption of factored strategies or other structured representations of a game model. We propose a principled method of managing generalization risk to derive the optimal game-theoretic model for the observed data in a restricted class of models. Application to a large dataset generated from a trading agent scenario validates the method.

This thesis considers engineering both protocols and strategies in multi-agent systems comprised of selfish, rational autonomous agents. Mechanisms dealing with failures as well as aspects of decentralisation are designed and applied to a multi-sensor network scenario. A model for designing strategies is also proposed and a risk-based strategy for a continuous double auctions designed.

Along with the convenience brought by the increasing usage of autonomous systems, unexpected accidents happened. These accidents emphasize the need for autonomous systems to possess the ability to recognize potential hazards, effectively communicate these hazards to human operators, and facilitate retrospective analyses. This ability, including recognition, prejudgment, post-analysis, and reasoning, falls within the realm of cognitive ability, which is important in improving the safety and outcomes in the decision-making process of such systems. In this paper, we present a foundational step toward addressing the safety challenges involving the cognitive ability of artificial agents. We study the interplay between knowledge and the cognitive ability of intelligent agents. The main technical result is a sound and complete bimodal logical system that describes the interplay between the knowledge and cognitive ability modalities.

Together we know how to achieve: An epistemic logic of know-how

A New Approach In Learning For Intelligent Multi Agent Systems

This paper surveys the interface between the two major logical trends that describe agents' intelligent interaction over time: dynamic epistemic logic (DEL) and epistemic temporal logic (ETL). The initial attempt to "merge" DEL and ETL was made in van Benthem et al. (Merging frameworks for interaction: DEL and ETL, 2007) and followed up by van Benthem et al. (J Phil Logic 38(5):491---526, 2009) and Hoshi (Epistemic dynamics and protocol information. Ph.D. thesis, Stanford University Stanford, 2009a). The merged framework provides a systematic comparison between these two logical systems and studies new logics of intelligent interaction. This paper presents the main results and the recent developments at the interface between DEL and ETL.

The notion of interchangeability has been introduced by John Nash in one of his original papers on equilibria. This paper studies properties of Nash equilibria interchangeability in cellular games that model behavior of infinite chain of homogeneous economic agents. The paper shows that there are games in which a strategy of any given player is interchangeable with strategies of players in an arbitrary large neighborhood of the given player, but is not interchangeable with the strategy of a remote player outside of the neighborhood. The main technical result is a sound and complete logical system describing universal properties of interchangeability common to all cellular games.

The paper presents semantically complete Hilbert-style systems for some variants of common sense modal predicate logic proposed by van Benthem and further developed by Seligman. The paper also investigates frame definability in the logics and shows what axiom schema is canonical in the logics. In addition to these semantic investigations on the logics, the paper provides the sequent calculi for some of the logics which enjoy cut elimination theorem.