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Model-based reflex agent. A model-based agent can handle partially observable environments. Its current state is stored inside the agent maintaining some kind of structure that describes the part of the world which cannot be seen. This knowledge about "how the world works" is called a model of the world, hence the name "model-based agent".
A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents. [1] Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. [2] Intelligence may include methodic, functional, procedural approaches ...
The belief–desire–intention software model (BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for ...
Multi-agent systems. An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems ...
Agent architecture. Agent architecture in computer science is a blueprint for software agents and intelligent control systems, depicting the arrangement of components. The architectures implemented by intelligent agents are referred to as cognitive architectures. [1] The term agent is a conceptual idea, but not defined precisely.
Soar [1] is a cognitive architecture, [2] originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University.. The goal of the Soar project is to develop the fixed computational building blocks necessary for general intelligent agents – agents that can perform a wide range of tasks and encode, use, and learn all types of knowledge to realize the full range of ...
The agent systems reference model (ASRM) is a layered, abstract description for multiagent systems. As such, the reference model. provides a taxonomy of terms, concepts and definitions to compare agent systems; identifies functional elements that are common in agent systems; captures data flow and dependencies among the functional elements in ...
e. In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves training a reward model to represent preferences, which can then be used to train other models through reinforcement learning. In classical reinforcement learning, an intelligent agent's goal ...