Multiagent reasoning with probability,time, and beliefs

Any agent interacting with the real world must be able to reason about uncertainty in the world, about the actions that may occur in the world (either due to the agent or those initiated by other agents), about the (probabilistic) beliefs of other agents, and how these (probabilistic) beliefs are changing over time. In this article, we develop a family of logics that a reasoning agent may use to perform successively more sophisticated types of reasoning in such environments. We also characterize different types of agents. Furthermore, we provide a logic that enables a systems designer (who may have populated an environment with a collection of such autonomous agents) to reason about the system of agents as a whole. © 1995 John Wiley & Sons, Inc.     

Bubble columns for condensation at high concentrations of noncondensable gas: Heat‐transfer model and experiments

Carrier gas based thermodynamic cycles are common in water desalination applications. These cycles often require condensation of water vapor out of the carrier gas stream. As the carrier gas is most likely a noncondensable gas present in very high concentrations (60–95%), a large additional resistance to heat transfer is present. It is proposed to reduce the aforementioned thermal resistance by condensing the vapor–gas mixture in a column of cold liquid rather than on a cold surface using a bubble column heat exchanger. A theoretical predictive model for estimating the heat‐transfer rates and new experimental data to validate this model are described. The model is purely physics based without the need for any adjustable parameters, and it is shown to predict heat rates within 0 to ?20% of the experimental values. The experiments demonstrate that heat‐transfer rates in the proposed device are up to an order magnitude higher than those achieved in existing state‐of‐the‐art dehumidifiers. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1780–1790, 2013     

Multifactor,Sequentially Releasing Scaffolds for Tissue Engineering:Fabrication Using Solvent/Nonsolvent Sintering Technology

Biodegradable constructs, providing both mechanical support to growing tissues and timed release of biological agents, are highly desired in tissue engineering. This study aimed to develop a platform technology that responds to these challenges. Accordingly, we report herein on model systems in which microspheres of poly(suberic anhydride), containing all-trans retinoic acid (atRA), and poly(d,l -lactic acid-co-glycolic acid), containing bovine serum albumin (BSA), were co-sintered at room temperature, using a solvent/nonsolvent mixture. These scaffolds release about 60% of atRA and negligible amounts of BSA within the first five days, followed by slower and steady release of BSA. They have pores of 150–500 μm and a compressive modulus of 200 kPa. Myoblasts and fibroblasts were seeded on the loaded scaffolds and both showed enhanced proliferation rates. Based on sound thermodynamic principles of polymer science, this technology demonstrates an as yet unachieved degree of versatility. It allows for the tailoring of “intelligent” scaffolds that preserve the integrity of the incorporated agents and of advanced modalities to release various drugs in a scheduled manner.     

Second law analysis of crossflow heat exchanger in the presence of axial dispersion in one fluid

In the present paper second law analysis of crossflow heat exchangers has been carried out in the presence of non-uniformity of flow. This non-uniformity is modeled with the help of axial dispersion model and takes into account the back mixing and flow maldistribution. An analytical model for exergy destruction has been evaluated for the cross-flow configuration. A wide range of study of the operating parameters and non-uniform flow on exergetic behavior of crossflow heat exchangers has been carried out. The results clearly bring out not only the reason behind the maximum entropy paradox in heat exchangers but also the proper perspective of exergy destruction and the consequent optimization of crossflow heat exchangers from the second law viewpoint.     

Investigation of Bubble Behavior in Subcooled Flow Boiling of Water in a Horizontal Annulus Using High-Speed Flow Visualization

Experiments have been carried out to study bubble behavior in subcooled flow boiling of water in a horizontal annulus at mass fluxes from 400 to 1200 kg/m²-s, heat fluxes from 0.1 to 1 MW/m², and pressures varying from 1 to 4 bar using high-speed visualization methods. National Instruments Labview IMAQ Vision Builder automated image-processing software was used to analyze the images obtained by high-speed visualization to obtain bubble size and bubble density. The parametric effects of pressure, mass flux, and heat flux on bubble behavior have also been brought out. Experimental results were validated by comparing with the predicted bubble sizes by using the Zeitoun and Shoukri (1996) correlation and were found to be in good agreement. It was found that bubble behavior is significantly affected by mass flux of working fluid and applied heat flux, whereas pressure of working fluid influences the bubble formation process indirectly.     

Computing the fault tolerance of multi-agent deployment

A deployment of a multi-agent system on a network refers to the placement of one or more copies of each agent on network hosts, in such a manner that the memory constraints of each node are satisfied. Finding the deployment that is most likely to tolerate faults (i.e. have at least one copy of each agent functioning and in communication with other agents) is a challenge. In this paper, we address the problem of finding the probability of survival of a deployment (i.e. the probability that a deployment will tolerate faults), under the assumption that node failures are independent. We show that the problem of computing the survival probability of a deployment is at least NP-hard. Moreover, it is hard to approximate. We produce two algorithms to accurately compute the probability of survival of a deployment—these algorithms are expectedly exponential. We also produce five heuristic algorithms to estimate survival probabilities—these algorithms work in acceptable time frames. We report on a detailed set of experiments to determine the conditions under which some of these algorithms perform better than the others.     

Temporal Reasoning for a Collaborative Planning Agent in a Dynamic Environment

We present a temporal reasoning mechanism for an individual agent situated in a dynamic environment such as the web and collaborating with other agents while interleaving planning and acting. Building a collaborative agent that can flexibly achieve its goals in changing environments requires a blending of real-time computing and AI technologies. Therefore, our mechanism consists of an Artificial Intelligence (AI) planning subsystem and a Real-Time (RT) scheduling subsystem. The AI planning subsystem is based on a model for collaborative planning. The AI planning subsystem generates a partial order plan dynamically. During the planning it sends the RT scheduling subsystem basic actions and time constraints. The RT scheduling subsystem receives the dynamic basic actions set with associated temporal constraints and inserts these actions into the agent's schedule of activities in such a way that the resulting schedule is feasible and satisfies the temporal constraints. Our mechanism allows the agent to construct its individual schedule independently. The mechanism handles various types of temporal constraints arising from individual activities and its collaborators. In contrast to other works on scheduling in planning systems which are either not appropriate for uncertain and dynamic environments or cannot be expanded for use in multi-agent systems, our mechanism enables the individual agent to determine the time of its activities in uncertain situations and to easily integrate its activities with the activities of other agents. We have proved that under certain conditions temporal reasoning mechanism of the AI planning subsystem is sound and complete. We show the results of several experiments on the system. The results demonstrate that interleave planning and acting in our environment is crucial.     

Negotiating with bounded rational agents in environments with incomplete information using an automated agent

Many tasks in day-to-day life involve interactions among several people. Many of these interactions involve negotiating over a desired outcome. Negotiation in and of itself is not an easy task, and it becomes more complex under conditions of incomplete information. For example, the parties do not know in advance the exact tradeoff of their counterparts between different outcomes. Furthermore information regarding the preferences of counterparts might only be elicited during the negotiation process itself. In this paper we propose a model for an automated negotiation agent capable of negotiating with bounded rational agents under conditions of incomplete information. We test this agent against people in two distinct domains, in order to verify that its model is generic, and thus can be adapted to any domain as long as the negotiators' preferences can be expressed in additive utilities. Our results indicate that the automated agent reaches more agreements and plays more effectively than its human counterparts. Moreover, in most of the cases, the automated agent achieves significantly better agreements, in terms of individual utility, than the human counterparts playing the same role.     

Beliefs, time and incomplete information in multiple encounter negotiations among autonomous agents

In negotiations among autonomous agents over resource allocation, beliefs about opponents, and about opponents’ beliefs, become particularly important when there is incomplete information. This paper considers interactions among self‐motivated, rational, and autonomous agents, each with its own utility function, and each seeking to maximize its expected utility. The paper expands upon previous work and focuses on incomplete information and multiple encounters among the agents. It presents a strategic model that takes into consideration the passage of time during the negotiation and also includes belief systems. The paper provides strategies for a wide range of situations. The framework satisfies the following criteria: symmetrical distribution, simplicity, instantaneously, efficiency and stability. This revised version was published online in June 2006 with corrections to the Cover Date.