Action selection is a process of decision making and behavioral choice studied in psychology, robotics, and artificial intelligence. Researchers observe and adapt instinctive reactions of living creatures to create controlled environments for study. The field is guided by strict guidelines and focuses on response time, with each successful experiment leading to a more complex argument.
Action selection is a process involving how an intelligently designed system will react to a given problem. It is usually a field studied in psychology, robotics and artificial intelligence. Action selection is synonymous with decision making and behavioral choice. The collected data is researched and broken down to be able to adapt it to artificial systems such as robotics, video games and artificial intelligence programming.
Much of the data in the life sciences can be observed and experienced to evoke a variable response. All living creatures have their own instinctive reaction to food, predators and mates. Creating a controlled environment in which studied animals are observed to always perform different solutions to different problems provides researchers and programmers with a foundation for the advancement of their study. This in turn has led researchers and programmers to try and recreate those gut responses in a controlled way.
For researchers and programmers, the most common questions used in stock selection are focused on what to do next and what happens next. The answers in turn can be recycled for a new batch of experimental action selection. Early examples of action selection can be found in games and artificial intelligence programming. In computer games, it can be found in first-person shooters (FPS) such as Halo and Counter-Strike. Creatures, a pet-based game, uses an AI engine that can make its own decisions by adapting to the tasks.
What makes action selection a unique field is that there is always a strict guide to follow in order to have an acceptable level of data. The guide would always be based on a subject that is modeled after a human or animal. For most, if not all researchers and programmers, a subject will always need to be placed in a location where the environment is unpredictable and ever-changing. The subject will also have to react in time while performing a series of tasks. He also has to interact with real humans to introduce a randomization factor.
With that many random factors and a strict guideline to follow, the research never ends as there will always be a different set of circumstances for any experiment. A primary factor that makes researchers and programmers study this field intensely is response time. With each successful experiment in which the subject has learned an action, a different course of action will emerge. This in turn makes for a more complex argument than a previous version.
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