What is intelligent agent and its types?

An intelligent agent (IA) refers to a software system that is able to autonomously perform tasks in the real world. In general, an intelligent agent can be thought of as a computer program that acts on behalf of its user or creator, making rational decisions and taking necessary action based on their programming and environment. Examples of intelligent agents include artificial intelligence programs, virtual assistants, autonomous robots, and search engine algorithms.

There are three main types of intelligent agents: reactive agents, limited memory agents, and goal-based agents.

Reactive Agents: Reactive Agents or “simple reflex agents” are the simplest type of IA because they do not possess any knowledge beyond what they experience in their environment. These programs rely solely on reactive behavior, meaning that they respond directly to observed conditions without considering past data or planning for future variables. For this reason, reactive agents often produce suboptimal performance when compared with more advanced AI models such as goal-based learning systems.

Limited Memory Agents: Limited memory agents possess some degree of “memory,” which allows them to learn from past experiences by storing information about their previous states in order to make better decisions later on. These types of IA can observe changing environments over time and adjust accordingly using acquired knowledge from prior situations or from additional training data input by human operators.. Examples of limited memory agents include supervised learning algorithms like decision trees and neural networks used for applications such as image recognition or natural language processing (NLP).

Goal-Based Agents: Goal-based AI systems collect information about their environment through exploration before reaching a target state where the desired outcome has been achieved — such as achieving a certain score in a game or navigating around obstacles — through trial and error methods combined with reinforcement learning principles. Unlike simple reflexes AIs which act solely based on immediate stimuli responses detected within the environment at any given moment in time , goal-oriented AI’s employ heuristics – mental shortcuts – that allow them utilize stored knowledge .

An intelligent agent is an autonomous program or device that can make decisions, observe its environment, and take actions to pursue particular goals. Intelligent agents are used in a variety of applications, from search engine algorithms to automated robotic systems. They can operate on their own or alongside other agents as part of a multi-agent system. Generally speaking, intelligent agents are defined by their abilities to perceive the environment and make decisions independently of external control.

Types of Intelligent Agents:
1) Reactive Agents: These agents act based solely on the current state they’re in; they don’t use any memory or history data for decision making or predicting outcomes. This type of agent is generally limited in capabilities since it has no sense of past events or understanding about long-term consequences for actions it takes today.
2) Limited Memory Agents: These agents have access to some restricted past experiences which they can use when taking decisions. While there is limitations on what these memories consist off, this type of agent exhibits more effective goal-oriented behaviors compared to reactive agents since they learn from previous decisions and adapt behavior accordingly when presented with new situations over time.
3) Theory Of Mind Agent: In addition to the ability to learn from past experiences and adapt behavior accordingly, this type of agent also possesses a degree human ‘understanding’—it knows how another person may be thinking & feeling at any given moment based on various cues such as body language & speech pattern etc., allowing them interact with humans much like we would interact with one another—a task impossible for purely reactive/memory limited agents alone!