1229519
A decision-theoretic approach for designing proactive communication in multi-agent teamwork
Techniques that support effective communication during teamwork processes are of particular importance. Psychological study shows that an effective team often can anticipate information exchange among the team and communicate relevant information proactively. Proactive communication is crucial for understanding and sharing common goals and for cooperative actions. Communication can be valuable if it assists agents with new and timely information; it also has cost because it consumes network resources such as bandwidth. To address these issues, we present a new model that uses information production and need to capture the complex multi-agent communication process and a dynamic decision-theoretic determination of communication strategies. We also introduce a generic utility function and an algorithm, DTPC (Decision-Theoretic Proactive Communication), that focuses on representing information production and need of team members and resolving decision interactions among them for making decisions.
40423470
Proactive Communication in Observation-Based Agent Team Corporation
16356479
A multi-agent simulation for social agents
Agent-based modeling of human social behavior is an increasingly important research area. Many fully functional multi-agent systems have been developed and have been put to use over the years. But efficient scalable and robust social systems are difficult to engineer, both from the modeling perspective and the implementation perspective. There exist three important difficulties. First, the system needs to have an adaptable agent framework that can successfully make intuitive and deliberative decisions much like a real social participant would. Secondly, the system must have a robust architecture that not only ensures its functioning no matter the simulation, but also provides an easily understood interface that researchers can interact with while running their simulations. Finally, the system must be effectively distributed to handle the necessary number of agents that social research requires to obtain meaningful results. This paper presents our work on creating a multi-agent simulation for social agents that would overcome these three difficulties. Lastly, we present a simulation to test the system and provide the results of that simulation.
5679790
Proactive Information Exchange During Team Cooperation
We are concerned, ultimately, with multi-agent teams involving both software and human agents in which the software agents assist in training the humans, e.g., as virtual team members. The software agents must be capable of utilizing the teamwork mechanisms used by humans. In this paper, we describe how to give agents the same implicit communication capabilities, i.e., observation, that humans use. We show how agents can use observations of the environment and teammates' actions to estimate other agents beliefs without bothering them with unnecessary messages; we also show how agents can anticipate information needs among the team and proactively exchange information, reducing the total communication volume. To achieve these goals, we add sensing capabilities to agents and present algorithms that infer teammates' mental state from the observation. Experimental data is presented that shows that the advantage of observation in proactive information exchange as well as enhanced team performance.
35439746
Role-Based and Agent-Oriental Teamwork Modeling
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.
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.
9609952
A survivable routing algorithm with differentiated domain protection based on a virtual topology graph in multi-domain optical networks
In this paper, we propose a novel differentiated domain protection (DDP) scheme to address survivability in multi-domain optical networks. Survivable routing in multi-domain networks is a challenging algorithmic problem because it requires choosing links that provide adequate protection both between domains and within domains that may offer different protection services. To satisfy the survivability requirements of different domains, DDP considers differentiated protection schemes, i.e., dedicated protection, shared protection, or no protection in different domains. In order to respect the principle of transparent management in multiple domains, DDP abstracts a multi-domain optical network to a virtual topology graph (VTG) for solving routing between domains. Simulation results show that DDP, unlike traditional schemes, can provide trade-off between protection methods and also allows better resource utilization.
129384413
Biomass measurements and relationships with Landsat‐7/ETM+ and JERS‐1/SAR data over Canada's western sub‐arctic and low arctic
Information on biomass distribution is needed to estimate GHG emissions and removals from land use changes in Canada's north for UNFCCC reporting. This paper reports aboveground biomass measurements along the Dempster Highway transect in 2004, and around Yellowknife and the Lupin Gold Mine in 2005. The measured aboveground biomass ranges are 10–100 t ha−1 for woodlands, 1–100 t ha−1 for shrub sites, and 0.5–10 t ha−1 for grass/herbs sites. The root mean squared error (RMSE) of measurements is 21%, and the median absolute percentage error (MedAPE) is 14%. The combination of JERS backscatter and Landsat TM4/TM5 gives the best biomass equation for the Dempster Highway transect, with r 2 = 0.72 when using a one‐step approach (i.e. using all points) and 0.78 when using a two‐step approach (i.e. stratifying data into three classes: grass, shrub, and woodlands). The two‐step approach reduces the MedAPE from 53% to 33%. The validation against Yellowknife & Lupin data indicates that the equations have good transferability. The improvement of two‐step approach over the one‐step approach, however, is not significant for the validation dataset, suggesting that the one‐step approach is as good as the two‐step approach when applied over areas outside where the equations are developed. The relationships and error analysis of this study, as well as the final estimate of GHG emission/removal over Canada's north have been incorporated into Canada's 2006 UNFCCC report.
7267319
Symbolic expression analysis for compiled communication
Enabling circuit switching in multiprocessor systems has the potential to achieve more efficient communication with lower cost compared to packet/wormhole switching. However, in order to accomplish this efficiently, assistance from the compiler is required to reveal the communication pattern in the parallel application. In this paper we present symbolic expression analysis techniques in a MPI parallel compiler. Symbolic expression analysis allows the identification and representation of the communication pattern and also assists in the determination of communication phases in MPI parallel applications at compile-time. We demonstrate that using the compiler analysis based on symbolic expression analysis to determine the communication pattern and phases provides an average of 2.6 times improvement in message delay over a threshold-based runtime system for our benchmarks with a maximum improvement of 9.7 times.
8620934
Certifying Concurrent Programs Using Transactional Memory
Transactional memory (TM) is a new promising concurrency-control mechanism that can avoid many of the pitfalls of the traditional lock-based techniques. TM systems handle data races between threads automatically so that programmers do not have to reason about the interaction of threads manually. TM provides a programming model that may make the development of multi-threaded programs easier. Much work has been done to explore the various implementation strategies of TM systems and to achieve better performance, but little has been done on how to formally reason about programs using TM and how to make sure that such reasoning is sound. In this paper, we focus on the semantics of transactional memory and present a proof-carrying code (PCC) system for reasoning about programs using TM. We formalize our reasoning with respect to the TM semantics, prove its soundness, and use examples to demonstrate its effectiveness.