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Computational intelligence methods are well-suited for use in computer controlled opponents for video games. In many other applications of these methods, the aim is to simulate near-optimal intelligent behaviour. But in video games, the aim is to provide interesting opponents for human players, not optimal ones. In this study, we trained neural network-based computer controlled opponents to play like...
The NetFlix Prize is a research contest that will award $1 Million to the first group to improve NetFlixpsilas movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of customers for movies. From this data, a processing scheme must be developed that can predict how a customer will rate a given movie on a scale of 1 to 5. An architecture is presented...
This study reveals the properties of the input/output relationship for a real-valued single-hidden layer feed-forward neural network (SLFN) with the tanh activation function on all hidden-layer nodes and the linear activation function on output node. Specifically, the rule-extraction of the SLFN is done through mathematically analyzing its preimage, which is the set of input values for a given output...
Past decades, numerous spectral analysis based algorithms have been proposed for dimensionality reduction, which plays an important role in machine learning and artificial intelligence. However, most of these existing algorithms are developed intuitively and pragmatically, i.e., on the base of the experience and knowledge of experts for their own purposes. Therefore, it will be more informative to...
Research in computational intelligence (CI) has produced a huge collection of algorithms, grouped into the main CI paradigms. Development of a new CI algorithm requires such algorithm to be thoroughly benchmarked against existing algorithms, which requires researchers to implement already published algorithms. This re-implementation of existing algorithms unnecessarily wastes valuable time, and may...
Artificial intelligence research is now flourishing which aims at achieving general, human-level intelligence. Accordingly, cognitive architectures are increasingly employed as blueprints for building intelligent agents to be endowed with various perceptive and cognitive abilities. This paper presents a novel integrated neuro-cognitive architecture (INCA) which emulate the putative functional aspects...
The aim of this paper is to offer mathematical proofs of Pawlakpsilas rough set theory about distributed knowledge based on rough sets and relational databases. A case study on actual self-reported geriatric data for survival analysis is presented to provide a computational evidence of the distributed knowledge. Risk factors, prolongation time prediction rules and validation are also computed and...
A problem solving domain for the application of artificial intelligence (AI) methods towards knowledge discovery for the purposes of modelling and forecasting is urban air quality. This domain has the specific characteristic that the key parameters of interest (pollutant concentration criteria) have multiple temporal (and spatial) scales. The present paper applies ANNs for the operational forecasting...
Current work is described wherein simplified versions of the Novamente cognition engine (NCE) are being used to control virtual agents in virtual worlds such as game engines and second life. In this context, an IRC (imitation-reinforcement-correction) methodology is being used to teach the agents various behaviors, including simple tricks and communicative acts. Here we describe how this work may...
Artificial emotion study will be of utmost importance in future artificial intelligence research. In this paper, an emotion understanding system based on brain activity and ldquoGISTrdquo is newly proposed to categorize emotions reflected by natural scenes. According to the strong relationship of human emotion and the brain activity, functional magnetic resonance imaging (fMRI) and electroencephalography...
Developing computer-controlled groups to engage in combat, control the use of limited resources, and create units and buildings in real-time strategy (RTS) games is a novel application in game AI. However, tightly controlled online commercial game pose challenges to researchers interested in observing player activities, constructing player strategy models, and developing practical AI technology in...
This paper presents a new way to combine two different approaches of artificial intelligence looking for the best path in a graph, ant colony optimization and Bayesian networks. The main objective is to develop a learning management system which will have the capability of adapting the learning path to the learnerpsilas needs in execution time, taking into account the pedagogical weight of each learning...
In the last two decades the advancement of AI/CI methods in classical board and card games (such as Chess, Checkers, Othello, Go, Poker, Bridge, ...) has been enormous. In nearly all ldquoworld famousrdquo board games humans have been decisively conquered by machines (actually Go remains almost the last redoubt of human supremacy). In the above perspective the natural question is whether there is...
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