Agents and the Semantic Web
Types of Environments
- Accessible vs. inaccessible: agent’s sensors give it access to the complete state of the environment at each point in time
- Deterministic vs. non-deterministic: next state of the environment is completely determined by the current state and the action executed by the agent
- Episodic vs. non-episodic: agent’s experience is divided into atomic episodes, each episode consisting of a perception-action pair where the action is a single action/event
- Static vs. dynamic: environment is unchanged during the agent’s deliberation of an action
- Discrete vs. continuous: limited number of distinct, clearly defined percepts and actions
- Single agent: the agent works in isolation (no other agents around)
Types of Agents
Reflex Agent simplest form, the agent merely reacts to its environment – no memory, no internal states, no planning
State-based Agent the next step up is an agent that keeps track of its current (and possibly previous) state(s), this can help with planning and understanding
Goal-oriented Agent this agent has the ability to plan out a sequence of states to achieve in order – planning might be based on a table-lookup approach or something more elaborate using a search mechanism and available planning knowledge
Utility-based Agent the agent has the ability to determine the usefulness of a plan step toward achieving its goals so that it can achieve the goals in a more optimal fashion, and possibly have better final results for goal
