A foraging environment for OpenAI Gym
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Updated
Mar 5, 2017 - Python
A foraging environment for OpenAI Gym
Animal behavior based on agents simulation
Quantify the diet composition in % by mass of prey found by analysing the content of samples (e.g. scats, stomachs), identify diet clusters, and measure interspecific overlap.
Identification of isotopic niches by considering both intra- and interindividual variability (a novel hierarchical Basyesian model). Measure the isotopic niche overlap. The method is ajusted to isotopic data with intra-individual variability (e.g. measures on whiskers, feathers, tooth).
Study on the role of body size, species identity, and functional traits on foraging area of herbivorous reef fishes
🐦🐜This repository contains simulations of emergent behavior such as the swarming behavior of flocking birds and schooling fish, as well as the foraging behavior of ant colonies.
Ant foraging simulation
statistical analyses for Psychological Research and then Cognitive Processing paper
A Python package to simulate multi-agent cognitive association tasks 🤖 🧠 👥
Ant Pheromone Trail Simulation
Forager is a web based application for mapping publicly accessible foods.
Simulation of evolutionary branching under optimal resource choice
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