17620967
Research on AI Planning Based Modeling Method for Area Traffic Signal Control
In this paper an area signal control model based on temporal planning is presented. Every activity of area signal control is modeled using planning domain definition language, and then the domain model of area signal control is established. Aiming at the representation problem of resource and time in the area signal control model, we extended the basic activity model by adding resource constraint and temporal constraint, and temporal planning based domain model for area signal control is established finally.
18823520
A Pursuit-Evasion Algorithm Based on Hierarchical Reinforcement Learning
This paper proposed a pursuit-evasion algorithm based on the Option method from hierarchical reinforcement learning and applied it into multi-robot pursuit-evasion game in 2D-Dynamic environment. The algorithm efficiency is studied by comparing it with Q-learning. We decompose the complex task with option method, and divide the learning process into two parts: High-level learning and Low-level learning, then design a new mechanism in order to make the learning process perform parallel. The simulation result shows the Option algorithm can efficiently reduce the complexity of pursuit-evasion task, avoid traditional reinforcement learning curse of dimensionality, and improve the learning result.
33934028
An FSM-Based Approach for Malicious Code Detection Using the Self-Relocation Gene
Most information attacks on the Internet are perpetrated by deploying malicious codes, which results in destructive epidemics. The correct execution of viruses and worms throughout the Internet is accomplished by self-relocation. Self-relocation is a built-in mechanism in most malicious codes, allowing them to get the base address of the host program to correctly infect it. Since most legitimate computer programs do not need self-relocate themselves, the detection of malicious codes could be reduced to the detection of the various mutations of the self-relocation gene. This study presents such a detection mechanism based on finite state machine theory for both known and previously unknown malicious executable codes. It does not rely on signature-screening of known viruses, but instead it detects self-relocation attempt of the suspicious executable code. The experiments were conducted and the results indicate that the proposed approach has better ability to detect known and previously unknown malicious executable codes than other methods.
18794722
Word Sense Language Model for Information Retrieval
This paper proposes a word sense language model based method for information retrieval. This method, differing from most of traditional ones, combines word senses defined in a thesaurus with a classic statistical model. The word sense language model regards the word sense as a form of linguistic knowledge, which is helpful in handling mismatch caused by synonym and data sparseness due to data limit. Experimental results based on TREC-Mandarin corpus show that this method gains 12.5% improvement on MAP over traditional tf-idf retrieval method but 5.82% decrease on MAP compared to a classic language model. A combination result of this method and the language model yields 8.92% and 7.93% increases over either respectively. We present analysis and discussions on the not-so-exciting results and conclude that a higher performance of word sense language model will owe to high accurate of word sense labeling. We believe that linguistic knowledge such as word sense of a thesaurus will help IR improve ultimately in many ways.
14243699
Research on the Hierarchical Supervisory Control of Underwater Glider
An underwater glider is a buoyancy-propelled and fixed-wing vehicle with attitude controlled completely by means of internal mass redistribution. In order to independently accomplish complex missions in unstructured and unknown oceanic environment, intelligent control system is needed to provide the underwater glider with the ability of active autonomy. Based on the RW (Ramadge & Wonham) supervisory control theory of discrete event dynamic system (DEDS), a three-level hierarchical supervisory control architecture for underwater glider is presented. The DEDS formalism models of underwater glider in terms of finite state automata (FSA) are built, and the realization of the hierarchical supervisory control (HSC) system is brought forth in detail. The simulation result shows that the three-level supervisory control system can adapt to uncertain undersea environment, and makes reasonable planning
14192001
Emergence of Social Norms in Complex Networks
This paper studies the problem that how social norms emerge even though agents are selfish and attempt to only maximize their own utility. We propose a new rule for social interactions. The rule is called Highest Rewarding Neighborhood (HRN). The HRN rule allows agents to remain selfish and be able to break relationships in order to maximize their utility. Our experiment shows that when agents are able to break unrewarding relationships that a Pareto-optimum strategy arises as the social normal. In addition we conclude the rate and amount of Pareto-optimum strategy that arises is dependent on the network structure when the networks are dynamic, and the rate is independent of the network structure when the networks are static.
7602241
Adaptation-based individualized face modeling for animation using displacement map
In this paper a new adaptation-based method is presented to reconstruct animatable facial models of human individuals from scan data. An anatomy-based generic control model serves as the starting point for our adaptation algorithm. Based on a series of measurements between the specified 3D landmarks, a global adaptation is carried out to align the generic control model to the scan surface. A local adaptation then deforms the geometry of the generic model to fit all of its vertices to the scan surface. The high-resolution geometry of the scan surface is represented as a displacement map which is generated using an offset-envelope mapping. Reconstruction of high-resolution geometry on the adapted generic mesh is achieved by hierarchical refinement using a surface subdivision scheme with resampling of the displacement map