Andere Kunden interessierten sich auch für
![The Law as a Moral Agent]( "The Law as a Moral Agent")
The Law as a Moral Agent44,99 €![An Arresting Life: Incidents and Accidents from Three Decades as a Cop and Secret Service Agent]( "An Arresting Life: Incidents and Accidents from Three Decades as a Cop and Secret Service Agent")
An Arresting Life: Incidents and Accidents from Three Decades as a Cop and Secret Service Agent27,99 €![Confessions of an Undercover Agent]( "Confessions of an Undercover Agent")
Confessions of an Undercover Agent25,99 €![Scared Fearless: An Unlikely Agent in the Us Secret Service]( "Scared Fearless: An Unlikely Agent in the Us Secret Service")
Scared Fearless: An Unlikely Agent in the Us Secret Service21,99 €![Marital Adjustment between Couples]( "Marital Adjustment between Couples")
Marital Adjustment between Couples27,99 €![The Role of ECOWAS in Conflict Resolution in Africa]( "The Role of ECOWAS in Conflict Resolution in Africa")
The Role of ECOWAS in Conflict Resolution in Africa36,99 €![Big Data Analytics]( "Big Data Analytics")
Big Data Analytics40,99 €
A Real-time Strategy (RTS) game is an adversarial game where the participants position and maneuver units and structures under their control to secure areas of the map and/or win by destroying their opponents' units and structures. It is possible to train new units and build new structures during the course of a game with limited amount of resources present in the setting. As opposed to comparable turn-based adversarial games such as chess and go, opponents do not wait for each others' moves so the game progresses naturally with units interacting each other in real time. As a result of the real-time nature of the game, the complexity of the game dramatically increases. In recent years, there has been an increasing interest in RTS games in the artificial intelligence community, especially from the perspective of reinforcement learning, to create an agent to play the RTS game, due to the problem's large state-action space. Modeling and implementing an efficient learning agent that is able to cope with the large state space is a difficult task.