40423470
Proactive Communication in Observation-Based Agent Team Corporation
2560128
Towards Human Decision-Making in Multi-Agent Systems
2 Decision theory finds its roots as a formal topic of research in the fields of economics and psychology. It traditionally relied upon the formal description of decision making embodied principle of maximum expected utility (EUT). But EUT can not capture the common human decision-making attitudes because it does not model the domain of human intuitions – thoughts or preferences that come to mind quickly and without much reflection. This paper models one human’s intuitive attitudes toward risk: risk-aversive and risk-seeking. Rather than immediately making a choice directly from the set of alternatives, agents first form an attitude concerning each possible alternative and likewise solve the corresponding decision problem with a preference order. Correspondingly, this preference order should not be constructed solely on the basis of the individual agent’s own attitudes but with the attitudes of all agents which are relevant. This paper presents our work on above two issues: capturing human intuitive decision-making under risk and extending it to social settings. Finally, we present two experiments that explore risk management behaviors of agents in social settings.
2366521
Observant and Proactive Communication in Multi-agent Teamwork
This paper investigates effective human team cooperation and incorporated the findings into multi-agent teamwork. We describe how to give agents the same cooperative capabilities, observability and proactivity, that humans use. We show how agents can use observation of the environment and of teammates' actions to estimate the teammates' beliefs without generating unnecessary messages; we also show how agents can anticipate information needs among the team members and proactively communicate the information. Finally, we present two experiments that explore the effectiveness and the scalability of the use of observability and proactivity.
2679883
Observation-based proactive communication in team cooperation
Observation and communication are important aspects of agent teamwork. We employ the agent's observability as the major means for individual agents to reason about the environment and other team members. We focus on how to represent agents' observability and how to include it into the basic reasoning for proactive communication. The syntax and the operational semantics of observability are given. Preliminary experiments are carried out to study the effectiveness of different aspects of observability.
30773646
The Performance of Erasure Codes Used in FT-MPI
22570791
A Novel Biology-Inspired Virus Detection Model with RVNS
A virus detection model based on artificial immune principles with real-valued negative selection (RVNS) is proposed. Feature vectors of program code are mapped into high dimension real-valued space. The architecture of this model, the formal definitions of self, nonself, antigen, antibody, and gene library are given. Then the process of self-tolerance of variable-sized detectors in real-valued space is discussed in detail. Variable-sized detectors provide concise representation of the detectors derived from benign files, which reduces the size of detectors set and advances the detection rate. The experimental results show that the model can detect obfuscated and firstly unknown virus more effectively than traditional model.
2191083
A Model of Context Awareness Agent System Based on Dynamic Fuzzy Logic
One of the main challenges of context-aware computing is how to elicit and represent complex, context-dependent requirements, and use the resulting representation within context-aware applications to support decision-making processes. In this paper, we describe context information with dynamic fuzzy logic and present an Agent-based context-aware system model. Unfortunately, there are often many errors that interfere in the Agent sensors, the process of each Agent communication and the sharing context information of each Agent. In order to robust the context awareness Agent system, we handle these errors with rewards mechanism, so that they do not interfere in the context information learning process. We consider an Agent decider that predicts stock price changes and uses its predictions for selecting actions. The simulation results demonstrate the validity and effectiveness of the proposed algorithm.
11500894
Using Reactive Deliberation for Real-Time Control of Soccer-Playing Robots
Soccer meets the requirements of the Situated Agent approach and as a task domain is sufficiently rich to support research integrating many branches of Al. Reactive deliberation is a robot architecture that combines responsiveness to the environment with intelligent decision making. Under Reactive Deliberation, the robot controller is partitioned into a deliberator and an executor; the distinction is primarily based on the different time scales of interaction. A controller for our team entry in the Robocup97 Simulation League, UBC Dynamo97, has been developed using the Reactive Deliberation architecture.
17517047
From range data to animated anatomy-based faces: a model adaptation method
This paper presents a new method for reconstructing animated, anatomy-based facial models of individuals from range data with minimal manual intervention. A prototype model with a multi-layer skin-muscle-skull structure serves as the starting point for our method. After the global adaptation, the skin mesh of the prototype model is represented as a dynamic deformable model which is deformed to fit scanned data according to internal force stemming from the elastic properties of the surface and external forces produced from the scanned data points and features. The underlying muscle layer that consists of three types of facial muscles is automatically adapted. According to the adapted skin and muscle structures, a set of automatically generated skull feature points is transformed to drive a volume morphing of the template skull model for skull fitting. The reconstructed model realistically reproduces the shape and features of a specific person and can be animated instantly.