Implementación en Python de un agente reactivo basado en modelo para Piedra-Papel-Tijera, con análisis del entorno de tareas y extensión a Lizard-Spock. Basado en Russell & Norvig.
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Jan 14, 2026 - Python
Implementación en Python de un agente reactivo basado en modelo para Piedra-Papel-Tijera, con análisis del entorno de tareas y extensión a Lizard-Spock. Basado en Russell & Norvig.
AI Laboratory coursework, demonstrating the practical application of intelligent agent architectures in game environments. The implementations serve as educational resources for understanding the evolution from reactive systems to learning-based artificial intelligence.
cleaning agent where the environment is partially observable
abc (artificial brain cortex) experimental dsl
Python Model Based Agent.
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