inverse reinforcement learning using evolutionary process. Reinforcement learning requires a large amount of time and learning convergence does not depend on the learning targets. In addition, if the learning targets are not known clearly, the appropriate reward cannot be defined and this makes learning difficult. Subgoal method and inverse reinforcement learning are effective for each problem. They can deal with the problem that it requires a large amount of time and finding appropriate reward is difficult. However, in case that there is interference between behavior rules, the learning is not achieved efficiently by the sub-goal method. Therefore, in this study, the process of learning each behavior rules simultaneously is made with evolutionary …show more content…
These robots need to control complex behavior. However, it is difficult for human to decide all actions. Therefore, the autonomous mobile robot learning the behavior rule personally is studied. One of the method to learn such behavior personally is reinforcement learning. Reinforcement Learning is the method of learning behaviors to maximize the value of the reward. The agent(the subject of decision-making) tries to find the action to the most reward. For example, in labyrinth task, the reward lies on the goal and solve the actions related on the more reward by trial and error. However, this method has two problems because it requires a large amount of time and learning does not converge depending on the learning targets. In addition, if the learning targets are not known clearly, the appropriate reward cannot be defined and this makes learning difficult. Setting sub-goals and dividing the environmental space is effective for achieving the final goal when the first problem occurs. Inverse reinforcement learning, which is a method that learns the reward function based on the behaviors of an expert agent, is known to solve the …show more content…
In particular, the skill required to achieve a final target is called a target skill. A sub-skill is a component skill of the target skill. Combinations of behaviors are required to achieve a sub-skill. Skill-based learning is the method that sub-skill is obtained and next sub-skill is learned using obtained sub-skills to achieve the final target. On the task with interference between behaviors in which a progress of a behavior is interferes a progress of other behaviors, learning of each behavior by subgoal method is not connected to achieving the final target. Therefore, learning with balance between behaviors is required for efficient learning method. The target of skill-based learning is to enable to learn the target skill in case with interference by setting sub-skills with balance between behaviors on the half way of the learning. A. Skill-based learning by inverse reinforcement learning using evolutionary process The problem how sub-skills are set is remained to realize skill-based learning. In this study, evolutionary process is used to obtain gradual sub-skills. The elite of evolutionary process can be used as sub-skills because it progress the skill
Artificial Intelligence (AI) is one of the newest fields in Science and Engineering. Work started in earnest soon after World War II, and the name itself was coined in 1956 by John McCarthy. Artificial Intelligence is an art of creating machines that perform functions that require intelligence when performed by people [Kurzweil, 1990]. It encompasses a huge variety of subfields, ranging from general (learning and perception) to the specific, such as playing chess, proving mathematical theorems, writing poetry, driving a car on the crowded street, and diagnosing diseases. Artificial Intelligence is relevant to any intellectual task; it is truly a Universal field. In future, intelligent machines will replace or enhance human’s capabilities in
This paper discusses three aspects of the field of robotics The first is the history of where the ideas of robotics originated. Second, what was the effect that these ideas had on society? Finally, what developments in the field have proved to be useful to society?
The Natural Human Learning Process is a process that the brain goes through when learning different skills. According to Dr. Smilkstein’s this process is divided into six steps. The first step is the motivation stage. This step is when the brain begins to gain the desire to do something for many different reasons. Sometimes, she says, we learn things because we feel as though “we have too”. The second step is the beginning practice step. This is the trial and error stage. The third step is the advanced practice stage, where you start doing the action over and over. The fourth step is the skillfulness stage, where you are starting to get really good at what you’re doing. You become more confident about your skill in this stage. The skill starts to become natural because the skill has been tried over continuously. The fifth step is the refinement stage. In this step you start to experiment with doing different things. For example the ingredients might change if the skill is cooking. In the last step mastery, is when the skill is able to be taught to others (Smilkstein).
In this paper I will be discussing the information I have learned from the article “From Positive Reinforcement to Positive Behaviors”, by Ellen A. Sigler and Shirley Aamidor. The authors stress the importance of positive reinforcement. The belief is that teachers and adults should be rewarding appropriate behaviors and ignoring the inappropriate ones. The authors’ beliefs are expressed by answering the following questions: Why use positive reinforcement?, Are we judging children’s behaviors?, Why do children behave in a certain way?, Do we teach children what to feel?, Does positive reinforcement really work?, and How does positive reinforcement work?. The following work is a summary of "Positive Reinforcement to Positive Behaviors" with my thoughts and reflection of the work in the end.
After this recent decade of advancement in robots, the question of how efficiently a robot makes decisions is still debated. Robots have various sensors that it takes into its central processing unit that influences its decisions. The development of gyroscopes allowed for the development of self-balancing robots and have given rise to modern day humanoid style robots. Robotic engineers can now design and teach robots various intelligent thought programmed patterns and skills to solve problems similar to humans since the technology can more resemble how humans perceive the world.
This paper will give a brief definition of the term Artificial Intelligence (AI). It will take an in-depth look at the origins and purpose of this exciting field in computer science. In particular, this paper will discuss a few of the many subcategories of research, applications and current technological obstacles that scientist face when developing AI. In addition, the author will look at AI’s various military specific applications for the purpose of training, target acquisition and command and control capabilities.
The science behind humanlike robots is advancing. They are becoming more smart, mobile and autonom...
Over the years mankind has advanced greatly in the field of technology and day by day we continue to advance. The future holds many possibilities, one of which is living in a world with robots. Isaac Asimov shared his view of this possible future in his novel I, Robot. His view portrays robots as machines superior to humans mentally and physically. If robots are superior to humans, how do humans control the robots? Humans create the three Laws of Robotics, which are instilled into the positronic brains of every robot created.
It is a shared truth that humans often tend to think of robots as nothing more than computer machines made of objects like metal, plastic, silicone and computer chips. However, in truth, a robot’s general purpose is more complex than some know. In order for a robot to function, it must carry out a set of arithmetic or logical operations, and programming the specs is difficult task that could take years to finish depending on the purpose of the robot.
The approach to artificial intelligence should be proceeded with caution. Throughout recent years and even decades before, it has been a technological dream to produce artificial intelligence. From movies, pop culture, and recent technological advancements, there is an obsession with robotics and their ability to perform actions that require human intelligence. Artificial intelligence has become a real and approachable realization today, but should be approached with care and diligence. Humans can create advanced artificial intelligence but should not because of the harm they may cause, the monumental advancement needed in the technology, and that its harm outweighs its benefits.
Therefore, according to the above a general process learning theory is sustainable even in the presence of biological constraints as behaviour can be reinforced and manipulated in most cases to acquire a desired behaviour.
Artificial Intelligence is the scientific theory to advance the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. This is going to hold the key in the future. It has always fa...
In this paper, I will be primarily focusing on the importance of feedback in learning. Practise is important to achieve goals but it cannot act alone, in order for a student to accomplish his/her goals he/she needs to practise; while practising it is important to receive feedback. By the end of this paper, I will try to prove why “Feedback is so important in learning”?
Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning tries to deal with this complicated task. In other words, machine learning is the branch of artificial intelligence that tries to find an answer to this question: how to make computer learn?
Robots are one of the artificial intelligence that made a breakthrough across all fields of life. In consequence, many research studies and projects regarding robots took place in the last decade. In addition, robots in the society could be one of the essential machines, due to their multitask system which could adjusted to any kind of performance. In general society could use these machines to fill manpower gap in short time with less cost. Therefore, robots can have huge positive effects on different fields of life such as emergency situations, daily chores, and manufacturing industry.