Oversight of reorganization in massive multiagent systems

Abstract. We have explored mechanisms for converting organizations to an edge type organization. Beyond structural differences, organizations differ in information flow network and information sharing strategies. We review organizational adaptation. A model of computational organization and reorganization is presented using dynamic roles. In addition to self-organization, our model allows human oversight and guided reorganization. This article lays a foundation for automatic organizational adaptation and human supervision. Our model is exemplified with simulated soccer

Radical Agent-based Approach for Intelligence Analysis

This paper presents a novel agent-based framework as a decision aid tool for intelligence analysis. This technology extends net-centric information processing and abstraction as well as fusion and multi-source integration strategies. Our information agents traverse and mediate disparate ontologies in different formats providing a foundation for semantic interoperability. The presented system provides knowledge discovery by accessing a large number of information sources in a particular domain and organizing them into a network of information agents. Each agent provides expertise on a specific topic by drawing on relevant information from other information agents in related knowledge domains. Unique advantages include net-centric scalability, principled information assurance, as well as ground breaking knowledge discovery in service of intelligence analysis

Improving Behavior of Computer Game Bots Using Fictitious Play

In modern computer games, "bots" -intelligent realistic agents play a prominent role in the popularity of a game in the market. Typically, bots are modeled using finite-state machine and then programmed via simple conditional statements which are hard-coded in bots logic. Since these bots have become quite predictable to an experienced games player, a player might lose interest in the game. We propose the use of a game theoretic based learning rule called fictitious play for improving behavior of these computer game bots which will make them less predictable and hence, more a enjoyable game

The Multifactor Model of the Agent’s Power in Social Networks

The analysis of social reasoning is at the core of understanding how to manage social networks. Since interpersonal relations are composed of multiple factors with different nature (i.e., structural and social factors), we explore their influence on the strategizing processes in social networks. We formalize interpersonal relations using the methods of structural and social analysis. As a part of the research, we develop the software application for the numerical visualization of the social network functioning based on the proposed mechanism