agent terminology the following terms are more frequently used in reinforcement learning in aiperformance measure of agentit is the criteriawhich determines how successful an agent is behavior of agentit is the action that agent performs after any given sequence of percepts perceptit is agent' perceptual inputs at given instance percept sequenceit is the history of all that an agent has perceived till date agent functionit is map from the precept sequence to an action environment some programs operate in an entirely artificial environment confined to keyboard inputdatabasecomputer file systems and character output on screen in contrastsome software agentssuch as software robots or softbotsexist in rich and unlimited softbot domains the simulator has very detailedand complex environment the software agent needs to choose from long array of actions in real time for examplea softbot designed to scan the online preferences of the customer and display interesting items to the customer works in the real as well as an artificial environment properties of environment the environment has multifold properties as discussed belowdiscrete/continuousif there are limited number of distinctclearly definedstates of the environmentthe environment is discrete otherwise it is continuous for examplechess is discrete environment and driving is continuous environment observable/partially observableif it is possible to determine the complete state of the environment at each time point from the perceptsit is observableotherwise it is only partially observable static/dynamicif the environment does not change while an agent is actingthen it is staticotherwise it is dynamic single agent/multiple agentsthe environment may contain other agents which may be of the same or different kind as that of the agent accessible/inaccessibleif the agent' sensory apparatus can have access to the complete state of the environmentthen the environment is accessible to that agentotherwise it is inaccessible deterministic/non-deterministicif the next state of the environment is completely determined by the current state and the actions of the agentthen the environment is deterministicotherwise it is non-deterministic episodic/non-episodicin an episodic environmenteach episode consists of the agent perceiving and then acting the quality of its action depends just on the episode itself subsequent episodes do not depend on the actions in the previous