Dane Kuiper

DIVAs 4.0: A Multi-Agent Based Simulation Framework

In this paper we present DIVAs 4.0, a framework that supports the development of large-scale agent-based simulation systems where agents are situated in open environments. DIVAs includes high-level abstractions for the definition of agents and open environments, a micro kernel for the management of the simulation workflow, domain-specific libraries for the rapid development of simulations, and reusable, extendable components for the control and visualization of simulations. We illustrate the use of DIVAs through the development of a simple simulator where virtual agents are situated in a virtual city.

Virtual Agent Perception in Multi-agent Based Simulation Systems

In this paper we discuss a modular multi-sense perception system for DIVAs virtual agents. It is based on the idea that local environmental in???uences are constantly sensed by one or more of an agent’s senses (sight, hearing, smell, etc.). The perception system is extensible and modifiable and allows users to dynamically modify how an agent perceives its environment at execution time. This paper focuses on the modularity of the agent perception architecture rather than the perception algorithms themselves.

Agent vision in multi-agent based simulation systems

In this paper, we propose virtual agent vision perception techniques to approximate realistic vision while maintaining low execution time. We discuss virtual agent vision in large scale multi-agent based simulations where agents are situated in open environments (i.e., inaccessible, non-deterministic, dynamic, continuous). When dealing with open environments, the efficiency of agent vision algorithms is of great importance since every agent’s perception must be calculated in simulated real-time. We discuss optimizations for vision algorithms in DIVAs, a large scale multi-agent based simulation framework.

Context-Aware Virtual Agents in Open Environments

This paper presents a model for the interaction between context-aware virtual agents and the environment in which they are situated. This model applies to multiagent based simulation systems dealing with human-like virtual agents in decentralized, continuous, and dynamic environments. The model supports an extensible agent perception module, allowing agents to perceive their environment through multiple senses (sight, hearing, smell, etc.). The environment reacts to agent influences as well as user-invoked stimuli by combining these influences to determine the next state of the environment. This paper introduces a formalization and an implementation of the model and discusses multiple scenarios involving context-aware virtual agents situated in dynamic environments.