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The modern school of Artificial Intelligence was originally expected to provide a full working model of intelligence as a set of procedures. Scholars implemented these procedures over time to conceptualize the notion of an intelligent machine. Computer scientists rushed to implement working models that would allegedly reach beyond many limits. Perhaps the most debilitating act was equating what is...
Due to the characteristics of web data and the change of men-machine interaction mode in the web age, artificial intelligence and information processing encounter new challenges and requirements. The new demand is that information processing has to deal with the meaning or semantics of information. Traditional information processing only treats the form of information rather than the meaning. Artificial...
It is recognized that the core problems across contemporary disciplines such as cognitive science, intelligence science, robotics, knowledge science, brain science, and computational intelligence are a fundamental mathematical problem where none of them may be simply reduced onto any type of numbers. This keynote lecture presents an emerging field known as mathematical engineering (ME) underpinning...
Brain inspired computing system is very important for building up real intelligent systems. In this talk, the current status and the recent progress of brain inspired computing research are introduced. The key challenges of this research including fundamental theory, neuromorphic chip design and fabrication, and software environment are analyzed. The possible solutions, development strategy and roadmap,...
The fundamental purpose for information study is to understand the properties of the objects in the world we live and to create the intelligent strategy for dealing with the objects so as to be able to achieve a win-win outcome between humans and the environment. What humans faced is the ontological information produced by the object and environment. For realizing the purpose mentioned above, humans...
Cooperative behavior is vital to Cognitive Radio Networks (CRN), which has the distributed nature. Time synchronization is the basic to cooperation. Many protocols are developed. However, they are either rather complicated or relying on infrastructure such as GPS. In this paper, a physical layer approach is proposed. Without complex protocols and not reliable to other systems, this approach has a...
The significant law of information conversion and intelligence creation, which is also a unified theory of information, knowledge and intelligence, is discovered recently and is presented in the paper for the first time. It is the author's belief that the law reported is of great significance to the understanding of the essence of Information Science, and of the information age as well.
The fuzzy and algebraic treatment of the hyperstructured logical variables and complex logical expressions are centric in inference methodologies of many contemporary disciplines such as cognitive informatics, cognitive computing, computational linguistics, cognitive semantics, causal inferences, computing with words, cognitive robotics, and computational intelligence. This paper presents a denotational...
The Street Engine is a new, highly parallel computer architecture designed specifically for cognitive computing. It executes a parallel production language directly in hardware with the aim of realising advanced cognitive agents more power efficiently than conventional computers. This paper describes the Street Engine and its native Street Language with a focus on those aspects that are different...
The paper deals with the problem of joint spectrum sensing and power control optimization for a multichannel, multiple-user cognitive radio network. In particular, we investigate trade-off factors in designing efficient spectrum sensing techniques to maximize the throughputs and minimize the interferences. To maximize the throughputs of secondary users and minimize the interferences to primary users,...
The problem of automated theorem finding is one of 33 basic research problems in automated reasoning which was originally proposed by Wos. The problem is still an open problem until now. Specific knowledge is the power of any scientist, therefore, if a scientist in a particular area takes part in the process of automated theorem finding, then the scientist should certainly make some contributions...
A novel Fine-grained Differential Harmony Search algorithm (FDHS) is presented in this paper. The new algorithm incorporates differential mutation scheme with the pitch adjustment operator of Harmony Search (HS) algorithm. Meanwhile a fine-grained evaluation strategy is adopted inside pitch adjustment on every dimension instead of construction completion. The innate self-adaptive feature of differential...
The work presented in this paper is part of the BAMBI project, which aims at better understanding natural cognition by designing non Von Neumann machines with biologicaly plausible hardware. Probabilistic programming allows artificial systems to better operate with uncertainty, and stochastic arithmetic provides a way to carry out approximate computations with few resources. As such, both are plausible...
This paper presents a cognitive feature extraction model based on scaling and multifractal dimension trajectory to analyze internet traffic time series. DNS (Domain Naming System) traffic time series is considered that contains tagged DNS Denial of Service attacks. The first step of the analysis involves transforming the DNS time series into a multifractal variance dimension trajectory keeping statistical...
The independent component analysis with reference algorithm uses gradient method to optimize the cost function, this makes it easily fall into local optimal solution. To overcome the problem, this paper proposes a new independent component analysis with reference algorithm that has global convergence. The new algorithm uses artificial fish swarm algorithm with global convergence to optimize cost function...
After a systematic review on psychological and neurophysiological studies, we propose a computational cognitive model for Chinese Sign Language (CSL) perception and comprehension with detailed algorithmic descriptions based on cognitive functionalities in human language processing. A semantic neural network based on this model is introduced as the knowledge representation method in CSL comprehension...
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