What are Reactive Agents?

Intelligent agents in AI that make decisions just based on the status of the environment at the moment without considering past performance or internal states are known as reactive agents. These agents just respond to the present circumstance by following a predetermined set of condition-action rules or a mapping function; they are devoid of any kind of memory or thinking ability.

According to the stimulus-response paradigm, reactive agents take in their surroundings and act instantly in reaction to any new information. Their behaviour is dictated by immediate sensory input and hard-coded rules or functions; they lack an explicit description of the environment or objectives.

Examples: Simple robots, thermostats, and reaction agents from video games are a few examples of reactive agent devices that react to particular circumstances without the need for long-term planning or memory.

Reactive vs Deliberative AI Agents

Reactive and deliberative agents represent two distinct paradigms within the field of Artificial Intelligence (AI), each offering unique approaches to decision-making and problem-solving. Let’s explore the key differences between reactive and deliberative agents

Similar Reads

What are Reactive Agents?

Intelligent agents in AI that make decisions just based on the status of the environment at the moment without considering past performance or internal states are known as reactive agents. These agents just respond to the present circumstance by following a predetermined set of condition-action rules or a mapping function; they are devoid of any kind of memory or thinking ability....

What are Deliberative Agents?

Conversely, deliberate agents are sentient entities with an internal state that can reason about their choices in response to information, objectives, and beliefs. Based on their observations and behaviours, these agents update their internal model of the environment....

Difference between Reactive and Deliberative Agents

Feature Reactive Agent Deliberative Agent World Model No internal model Maintains an internal world model Decision Making Based on current state and simple rules Based on planning and reasoning Memory Stateless Stateful Response Time Fast Slower Adaptability Limited Can learn and adapt Complexity Simple Complex...

Conclusion

Two different approaches to AI design are represented by reactive and deliberative agents. While deliberative agents do well at complicated activities involving preparation and reasoning, reactive agents are effective at basic tasks needing immediate replies. The particular needs of the application will determine which option is best....

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