Search Results for "physical"

...It combines computer vision with OpenStreetMap data, elevation models, satellite imagery, and street-level photographs to investigate possible locations. The system can analyze images even when GPS metadata, recognizable landmarks, or readable signs are unavailable. It evaluates physical clues such as mountain skylines, bridge geometry, shadows, and structural distances to narrow the search. Specialized Python scripts collect, score, and rank geographic candidates before the AI agent evaluates the strongest matches. Results include estimated coordinates, camera direction, confidence levels, and supporting visual evidence. ...

ChemCrow is an AI-powered framework designed to assist in chemical research and discovery. It integrates AI models with chemical knowledge bases to provide intelligent recommendations for synthesis planning, reaction prediction, and material discovery. This tool helps automate and accelerate research in computational chemistry and drug development.

...The "basic_EFSSM" version uses only state-oriented programming for agents. (Available soon.) --- Ribas-Xirgo, Ll.: Multi-agent system model of taxi fleets. In Advances in Physical Agents II, Springer International Publishing, 2021. Proceedings of the 21st International Workshop of Physical Agents (WAF 2020), November 19-20, 2020, Alcalá de Henares, Madrid, Spain.

...To resolve the concurrency issues within the maps representation and the meso-micro transitions, Simultra combines an event-based mesoscopic model of the maps with a more detailed physical engine.

Spark is a physical simulation system. The primary purpose of this system is to provide a *generic* simulator for different kinds of simulations. In these simulations, agents can participate as external processes.

TinyCog is a cognitive architecture (perception, action, reasoning, planning, and language) with a focus on representing "self-models" (physical, capabilities, intentions, social, historical, "cognitive stream") in order to implement social reasoning and collaborative planning in a "hunter domain" test bed. We use Prolog, RDF Triples, Description Logic and a HTN-Planner as base technologies.

Springbots is a python application which takes a set of 2d physical structures built with nodes and movable springs and evolve them for specific tasks like walking, swimming and jumping using genetic algorithm.

A-Life CAD is a toolkit providing a graphical interface for designing autonomous agents that can be linked against an AI game engine. Though it focuses on creating boid-like behaviours, it can also be used for physical simulation or swarm optimisation.