agentsanimals

Agentsanimals is a term used in computer science and ecology to denote a class of autonomous software agents that simulate animal-like behavior within an artificial environment. The concept combines agent-based modeling with principles from animal ecology and ethology to study how simple rules at the individual level produce complex system dynamics.

In these models, each agent has sensors, a state, and decision rules that govern actions such as foraging, movement, social interaction, reproduction, and predator avoidance. Agents may follow fixed rule sets, probabilistic choices, or learning components, allowing adaptive behavior. The environment can be a grid, continuous space, or network; resources, landscapes, and interactions with other agents influence decisions. Emergent patterns such as herd movement, territorial boundaries, or flocking can arise from local interactions.

Applications include ecological research, epidemiology, urban crowd dynamics, and educational simulations in classrooms and museums. In digital games and research platforms, agentsanimals provide believable animal dynamics and assist in exploring questions about cooperation, competition, and resource use.

Modeling considerations include calibration to real-world data, balancing realism with computational cost, validating emergent phenomena, and avoiding excessive anthropomorphism. Ethical and ecological questions about the fidelity and potential misuse of simulations are also discussed.

Common tools used to implement agentsanimals include NetLogo, Repast, MASON, GAMA, and Mesa. The term is not universally standardized and is primarily used to describe a subset of agent-based models that emphasize animal-like agents within ecological or behavioral contexts.