AI is at an impasse. It is stuck, or downsizing. Unable to build large, ambitious systems because no means to manage complexity. Now people manage complexity, but a large AI must do it itself. An AI must be able to tell for itself when it is right and when it is wrong. Experience is the route to this... Experience should be at the center of AI. It is what AI is about. It is the data of AI, yet ...

The General AI Challenge is an initiative to encourage the wider artificial intelligence community to focus on important problems in building intelligent machines with more general scope than is currently possible. The challenge comprises of multiple rounds, with the first round focusing on gradual learning, i.e. the ability to re-use already learned knowledge for efficiently learning to solve ...

The human brain is the best example of intelligence known, with unsurpassed ability for complex, real-time interaction with a dynamic world. AI researchers trying to imitate its remarkable functionality will benefit by learning more about neuroscience, and the differences between Natural and Artificial Intelligence. Steps that will allow AI researchers to pursue a more braininspired approach to...

Artificial Intelligence (AI) is useful. AI can deliver more functionality for reduced cost. AI should be used more widely but won’t be unless developers can trust adaptive, nondeterministic, or complex AI systems. Verification and validation is one method used by software analysts to gain that trust. AI systems have features that make them hard to check using conventional V&Vmethods. Neverthele...

Interactive conversation agents or CAs are computer programs or application software designed to simulate conversation with one or more human users in natural language. Providing CAs with knowledge, intelligence and humanoid interface has allowed them to be used in several practical applications. This paper presented the development and its performance of the interactive CAs called Artificial I...

Game Artificial Intelligence requires an interactive AI, which by its very nature presents many challenges to game developers. As AI tasks become more complex, the need to manage the execution of those tasks becomes more important. All but the most complex routines can be managed with some simple abstractions for execution management. These abstractions, through extension, could be used to map ...

If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do. If you are a video game developer, you should look to AI for the technology that makes completely new types of games possible. This chapter lays out the case for both of these propositions. It asks the question “what can video games do for AI”, and discusses how in particular ...

During AFs first decade (1956-1966), the task environments in which AI scientists investigated their basic science issues were generally idealized "clean" task environments, such as propositional calculus theorem proving and puzzle solving. After the mid-19605, a bolder and more applied inclination to choose complex real-world problems as task environments became evident. These efforts were bot...

The early promise of the impact of machine intelligence did not involve the partitioning of the nascent field of Artificial Intelligence. The founders of AI envisioned the notion of embedded intelligence as being conjoined between perception, reasoning and actuation. Yet over the years the fields of AI and Robotics drifted apart. Practitioners of AI focused on problems and algorithms abstracted...

There is no review paper available on Artificial Intelligence (AI) applications to e-commerce to the best of knowledge. This paper is a survey of various AI techniques that are used in the design and development of ecommerce systems. The techniques are categorized into three groups namely, AI techniques for B2B ecommerce, AI techniques for B2C e-commerce, and AI techniques for both B2B and B2C ...