University of Massachusetts Amherst

About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.

Improving Elevator Performance Using Reinforcement Learning

Abstract: This paper describes the application of reinforcement learning (RL) to the difficult real world problem of elevator dispatching. The elevator domain poses a combination of challenges not seen in most RL research to date. Elevator systems operate in continuous state spaces and in continuous time as discrete event dynamic systems. Their states are not fully observable and they are nonstationary due to changing passenger arrival rates. In addition, we use a team of RL agents, each of which is responsible for controlling one elevator car. The team receives a global reinforcement signal which appears noisy to each agent due to the effects of the actions of the other agents, the random nature of the arrivals and the incomplete observation of the state. In spite of these complications, we show results that in simulation surpass the best of the heuristic elevator control algorithms of which we are aware. These results demonstrate the power of RL on a very large scale stochastic dynamic optimization problem of practical utility.

Knowledge and the Prediction of Behavior: The Role of Information Accuracy in the Theory of Planned Behavior

Abstract: The results of the present research question the common assumption that being well informed is a prerequisite for effective action to produce desired outcomes. In Study 1 (N = 79), environmental knowledge had no effect on energy conservation, and in Study 2 (N = 79), alcohol knowledge was unrelated to drinking behavior. Such disappointing correlations may result from an inappropriate focus on accuracy of information at the expense of its relevance to and support for the behavior. Study 3 (N = 85) obtained a positive correlation between knowledge and pro-Muslim behavior, but Study 4 (N = 89) confirmed the proposition that this correlation arose because responses on the knowledge test reflected underlying attitudes. Study 4 also showed that the correlation could become positive or negative by appropriate selection of questions for the knowledge test. The theory of planned behavior (Ajzen, 1991), with its focus on specific actions, predicted intentions and behavior in all four studies.

Real-time databases

Abstract: Data in real-time databases has to be logically consistent as well as temporally consistent. The latter arises from the need to preserve the temporal validity of data items that reflect the state of the environment that is being controlled by the system. Some of the timing constraints on the transactions that process real-time data come from this need. These constraints, in turn, necessitate time-cognizant transaction processing so that transactions can be processed to meet their deadlines.

Agile dynamic provisioning of multi-tier Internet applications

Abstract: Dynamic capacity provisioning is a useful technique for handling the multi-time-scale variations seen in Internet workloads. In this article, we propose a novel dynamic provisioning technique for multi-tier Internet applications that employs (1) a flexible queuing model to determine how much of the resources to allocate to each tier of the application, and (2) a combination of predictive and reactive methods that determine when to provision these resources, both at large and small time scales. We propose a novel data center architecture based on virtual machine monitors to reduce provisioning overheads. Our experiments on a forty-machine Xen/Linux-based hosting platform demonstrate the responsiveness of our technique in handling dynamic workloads. In one scenario where a flash crowd caused the workload of a three-tier application to double, our technique was able to double the application capacity within five minutes, thus maintaining response-time targets. Our technique also reduced the overhead of switching servers across applications from several minutes to less than a second, while meeting the performance targets of residual sessions.