The recent success of machine learning has lead to advancements in robot intelligence and human-robot interaction. It is reported that robots can well understand visual scene information and describe the scenes in language using computer vision and natural language processing methods. Image Question-Answering (QA) systems can be used for human-robot interaction. However, to achieve human-level ...

The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more effective and richer cognitive computational models, and to a better understanding of the processes of artificial intelligence across the field. This paper presents a new model for the representation, computation, and lear...

using image processing and artificial intelligence systems in agriculture and food industry is increasing daily. the purpose of this research is to study the feasibility of using image processing technique in predicting process of moisture content changes on green tea sheets during the drying using predictive artificial intelligence systems such as: artificial neural networks and adaptive neuro...

At present, The network collaborative learning in education has been widely used, but they have some problems were not resolved, which like lacks intelligence or can not accurately master information requirements. In the research, using intelligent agent technology in the field of distributed artificial intelligence, to propose a model in collaborative learning process. The model based on the l...

Techniques from artificial intelligence have been widely applied in optical communication and networks, evolving early machine learning (ML) to the recent deep (DL). This paper focuses on state-of-the-art DL algorithms aims highlight contributions of communications. Considering characteristics different data types, we review multiple DL-enabled solutions communication. First, a convolutional ne...

We explore computational approaches for artificial agents to play the ultimatum game. We compare our agents’ behavior with that predicted by classical game theory, as well as behavior found in experimental (or behavioral) economics investigations. In particular, we study the following questions: How do artificial agents perform in playing the ultimatum game against fixed rules, dynamic rules, a...

After many false starts, the potential advantages of artificial intelligence for education are starting to appear. It remains in question, though, whether current theoretical frameworks are adequate for understanding processes of learning with artificial intelligence. This paper re-examines a recent study of children telling stories in collaboration with a virtual conversational agent, in which...

Building an intelligent agent, which simulates human-level learning appropriate for learning math, science, or a second language, could potentially benefit both education in understanding human learning, and artificial intelligence in creating human-level intelligence. Recently, we have proposed an efficient approach to acquiring procedural knowledge using transfer learning. However, it operate...