Modeling the Evolution of Companies using Intelligent Software Agents Architecture

The paper presents the concept of multi agent system that models the evolution of a company. The opportunity of such an approach and the limits of mathematical modeling are presented. The main players on the market are modeled as cognitive, adaptive, heterogeneous agents and evolve in a dynamic environment. The purpose is to use the model of operational agent that has these characteristics. This model is based on using an ATN (Augmented Transition Network) to adapt the behavior of its agent to the changes it detects in its environment. Each agent has an inference mechanism for the first order reasoning. The agents communicate between them through messages and will be implemented in a non synchronized object environment.multiagent system, economic model, discret events

Analytical Model for Constructing Deliberative Agents.

This paper introduces a robust mathematical formalism for the definition of deliberative agents implemented using a case-based reasoning system. The concept behind deliberative agents is introduced and the case-based reasoning model is described using this analytical formalism. Variational calculus is used during the reasoning process to identify the problem solution. The agent may use variational calculus to generate plans and modify them at execution time, so they can react to environmental changes in real time. Reflecting the continuous development in the tourism industry as it adapts to new technology, the paper includes the formalisation of an agent developed to assist potential tourists in the organisation of their holidays and to enable them to modify their schedules on the move using wireless communication systems

Representing and Reasoning about Dynamic Multi-Agent Domains: An Action Language Approach

abstract: Reasoning about actions forms the basis of many tasks such as prediction, planning, and diagnosis in a dynamic domain. Within the reasoning about actions community, a broad class of languages, called action languages, has been developed together with a methodology for their use in representing and reasoning about dynamic domains. With a few notable exceptions, the focus of these efforts has largely centered around single-agent systems. Agents rarely operate in a vacuum however, and almost in parallel, substantial work has been done within the dynamic epistemic logic community towards understanding how the actions of an agent may effect not just his own knowledge and/or beliefs, but those of his fellow agents as well. What is less understood by both communities is how to represent and reason about both the direct and indirect effects of both ontic and epistemic actions within a multi-agent setting. This dissertation presents ongoing research towards a framework for representing and reasoning about dynamic multi-agent domains involving both classes of actions. The contributions of this work are as follows: the formulation of a precise mathematical model of a dynamic multi-agent domain based on the notion of a transition diagram; the development of the multi-agent action languages mA+ and mAL based upon this model, as well as preliminary investigations of their properties and implementations via logic programming under the answer set semantics; precise formulations of the temporal projection, and planning problems within a multi-agent context; and an investigation of the application of the proposed approach to the representation of, and reasoning about, scenarios involving the modalities of knowledge and belief.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Synthetizing Qualitative (Logical) Patterns for Pedestrian Simulation from Data

This work introduces a (qualitative) data-driven framework to extract patterns of pedestrian behaviour and synthesize Agent-Based Models. The idea consists in obtaining a rule-based model of pedestrian behaviour by means of automated methods from data mining. In order to extract qualitative rules from data, a mathematical theory called Formal Concept Analysis (FCA) is used. FCA also provides tools for implicational reasoning, which facilitates the design of qualitative simulations from both, observations and other models of pedestrian mobility. The robustness of the method on a general agent-based setting of movable agents within a grid is shown.Ministerio de Economía y Competitividad TIN2013-41086-

The "Artificial Mathematician" Objection: Exploring the (Im)possibility of Automating Mathematical Understanding

Reuben Hersh confided to us that, about forty years ago, the late Paul Cohen predicted to him that at some unspecified point in the future, mathematicians would be replaced by computers. Rather than focus on computers replacing mathematicians, however, our aim is to consider the (im)possibility of human mathematicians being joined by “artificial mathematicians” in the proving practice—not just as a method of inquiry but as a fellow inquirer

On the Rationality of Escalation

Escalation is a typical feature of infinite games. Therefore tools conceived for studying infinite mathematical structures, namely those deriving from coinduction are essential. Here we use coinduction, or backward coinduction (to show its connection with the same concept for finite games) to study carefully and formally the infinite games especially those called dollar auctions, which are considered as the paradigm of escalation. Unlike what is commonly admitted, we show that, provided one assumes that the other agent will always stop, bidding is rational, because it results in a subgame perfect equilibrium. We show that this is not the only rational strategy profile (the only subgame perfect equilibrium). Indeed if an agent stops and will stop at every step, we claim that he is rational as well, if one admits that his opponent will never stop, because this corresponds to a subgame perfect equilibrium. Amazingly, in the infinite dollar auction game, the behavior in which both agents stop at each step is not a Nash equilibrium, hence is not a subgame perfect equilibrium, hence is not rational.Comment: 19 p. This paper is a duplicate of arXiv:1004.525

(WP 2020-01) The Sea Battle Tomorrow: The Identity of Reflexive Economic Agents

This paper develops a conception of reflexive economic agents as an alternative to the standard utility conception, and explains individual identity in terms of how agents adjust to change in a self-organizing way, an idea developed from Herbert Simon. The paper distinguishes closed equilibrium and open process conceptions of the economy, and argues the former fails to explain time in a before-and-after sense in connection with Aristotle’s sea battle problem. A causal model is developed to represent the process conception, and a structure-agency understanding of the adjustment behavior of reflexive economic agents is illustrated using Merton’s self-fulfilling prophecy analysis. Simon’s account of how adjustment behavior has stopping points is then shown to underlie how agents’ identities are disrupted and then self-organized, and the identity analysis this involves is applied to the different identity models of Merton, Ross, Arthur, and Kirman. Finally, the self-organization idea is linked to the recent ‘preference purification’ debate in bounded rationality theory regarding the ‘inner rational agent trapped in an outer psychological shell,’ and it is argued that the behavior of self-organizing agents involves them taking positions toward their own individual identities

Mathematical Explanation: A Contextual Approach

PurposeIn this article, we aim to present and defend a contextual approach to mathematical explanation.MethodTo do this, we introduce an epistemic reading of mathematical explanation.ResultsThe epistemic reading not only clarifies the link between mathematical explanation and mathematical understanding, but also allows us to explicate some contextual factors governing explanation. We then show how several accounts of mathematical explanation can be read in this approach.ConclusionThe contextual approach defended here clears up the notion of explanation and pushes us towards a pluralist vision on mathematical explanation

On the emergent Semantic Web and overlooked issues

The emergent Semantic Web, despite being in its infancy, has already received a lotof attention from academia and industry. This resulted in an abundance of prototype systems and discussion most of which are centred around the underlying infrastructure. However, when we critically review the work done to date we realise that there is little discussion with respect to the vision of the Semantic Web. In particular, there is an observed dearth of discussion on how to deliver knowledge sharing in an environment such as the Semantic Web in effective and efficient manners. There are a lot of overlooked issues, associated with agents and trust to hidden assumptions made with respect to knowledge representation and robust reasoning in a distributed environment. These issues could potentially hinder further development if not considered at the early stages of designing Semantic Web systems. In this perspectives paper, we aim to help engineers and practitioners of the Semantic Web by raising awareness of these issues