Other

Industrial Technology Institute

Newvectors LLC

Atarum Institute

John A Sauter

Sven Brueckner

Henry Van Dyke Parunak

H Van Dyke Parunak

Allen C Ward

Steven M Brophy

Mark E Brown

Peter K Hickman

John F White

Robert J Bisson

Robert P Judd

Robert S Matthews

A method of predicting the behavior of software agents in a simulated environment involves modeling a plurality of software agents representing entities to be analyzed, which may be human beings. Using a set of parameters that governs the behavior of the agents, the internal state of at least one of the agents is estimated by its behavior in the simulation, including its movement within the environment. This facilitates a prediction of the likely future behavior of the agent based solely upon its internal state; that is, without recourse to any intentional agent communications. In the preferred embodiment the simulated environment is based upon a digital pheromone infrastructure. The simulation integrates knowledge of threat regions, a cognitive analysis of the agent's beliefs, desires, and intentions, a model of the agent's emotional disposition and state, and the dynamics of interactions with the environment. By evolving agents in this rich environment, we can fit their internal state to their observed behavior. In realistic wargame scenarios, the system successfully detects deliberately played emotions and makes reasonable predictions about the entities' future behavior.

Characterizing and predicting agents via multi-agent evolution

A system and process uses pheromone propagation to provide direction and/or distance information to a remote destination through the use of localized decision making processes. Locally available information is exchanged and translated with global information through the use of a pheromone vocabulary and multi-layer grid systems. Self-organizing networks of sensors provide remote monitoring of a space.

Spatial coordination system

An apparatus for determining assignments to attributes (e.g., electrical power or overall dimensional size) of components within a system. A computerized constraint network is constructed which uses constraint agents, variable agents, and task agents in order to make assignments to the attributes of the components based upon market-based constraint optimization techniques. The attributes have variables indicative of the assignments to the attributes. Constraint data structures assist the agents in determining permissible assignments for the variables. The constraint data structures use preferential rules for determining the assignments to the variables. The preferential rules indicate which assignments for the variables of the agents produce higher utility and lower cost.

Computerized system for market-based constraint optimization

A method and apparatus are disclosed which allows a plurality of dissimilar simulation systems to act in a cooperative manner such that they may act to provide a single overall simulation of a system. The system to be simulated is partitioned into these simulation systems and subsequently these systems are networked and synchronized. This interaction of these dissimilar simulation systems is accomplished by a simulation tool which allows a simulation system to route messages to other systems, synchronizes the operation of all simulation systems, allows partitioning elements to be stored and downloaded to these systems, and allows each simulation system to utilize its own native programming language during the creation of the single system simulation associated therewith.

System for combining originally software incompatible control,

Growing community of inventors

Ann Arbor, MI, United States of America

John A Sauter