APPENDIX D SOFTWARE (INTELLIGENT) AGENTS Since the early 1990s, software agents—also known as intelligent agents, know-bots, softbots, or bots for short—have been. Identify and discuss two characteristics of intelligent agents. To create paragraphs in your essay response, type. At the beginning of the paragraph, and.

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May be able to help recruit an expert. (October 2009) In, an intelligent agent ( IA) is an entity which observes through sensors and acts upon an using actuators (i.e. It is an ) and directs its activity towards achieving goals (i.e. It is ', as defined in ). Intelligent agents may also or use to achieve their goals. They may be very simple.

A reflex machine, such as a, is considered an example of an intelligent agent. Simple reflex agent Intelligent agents are often described schematically as an abstract functional system similar to a. For this reason, intelligent agents are sometimes called abstract intelligent agents ( AIA) [ ] to distinguish them from their real world implementations as computer systems, biological systems, or organizations. Some definitions of intelligent agents emphasize their, and so prefer the term autonomous intelligent agents. Still others (notably ) considered goal-directed behavior as the essence of intelligence and so prefer a term borrowed from, '.

Intelligent agents in artificial intelligence are closely related to in, and versions of the intelligent agent paradigm are studied in,, the philosophy of, as well as in many and computer. Intelligent agents are also closely related to (an autonomous computer program that carries out tasks on behalf of users). In, the term intelligent agent may be used to refer to a software agent that has some intelligence, regardless if it is not a rational agent by Russell and Norvig's definition. For example, autonomous programs used for operator assistance or (sometimes referred to as ) are also called 'intelligent agents'. A general learning agent group agents into five classes based on their degree of perceived intelligence and capability: • simple reflex agents • model-based reflex agents • goal-based agents • utility-based agents • learning agents Simple reflex agents [ ] Simple reflex agents act only on the basis of the current percept, ignoring the rest of the percept history. The agent function is based on the condition-action rule: if condition then action.

This agent function only succeeds when the environment is fully observable. Some reflex agents can also contain information on their current state which allows them to disregard conditions whose actuators are already triggered.

Infinite loops are often unavoidable for simple reflex agents operating in partially observable environments. Note: If the agent can randomize its actions, it may be possible to escape from infinite loops. Model-based reflex agents [ ] A model-based agent can handle partially observable environments. Its current state is stored inside the agent maintaining some kind of structure which 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 model-based reflex agent should maintain some sort of that depends on the percept history and thereby reflects at least some of the unobserved aspects of the current state.

Msa Toxgard Ii Manual. Percept history and impact of action on the environment can be determined by using internal model. It then chooses an action in the same way as reflex agent. Goal-based agents [ ] Goal-based agents further expand on the capabilities of the model-based agents, by using 'goal' information. Goal information describes situations that are desirable.