14133109
Representing and executing protocols as joint actions
Families of conversation protocols can be expressed formally as partially ordered landmarks where the landmarks represent the state of affairs that must be brought about during the goal-directed execution of a protocol. Then, concrete protocols represented as joint action expressions can be derived from the partially ordered landmarks and executed directly by joint intention interpreters, thus nearly eliminating the need to implement a separate protocol handling system. This approach also supports (1) flexibility in the actions used to achieve landmarks, (2) shortcutting protocol execution, and (3) application of the joint intention theory to provide automatic exception handling along with a correctness criterion for protocols.
10504344
The adaptive agent architecture: achieving fault-tolerance using persistent broker teams
Brokered multi-agent systems can be incapacitated and rendered non-functional when the brokers become inaccessible due to failures that can occur in any distributed software system. We propose that the theory of teamwork can be used to specify robust brokered architectures that can recover from broker failures, and we present the adaptive agent architecture (AAA) to show the feasibility of this approach. The previous teamwork theory based on joint intentions assumes that team members remain in a team as long as the team exists. We extend this theory to allow dynamic broker teams whose members can change with time. We also introduce a theory of restorative maintenance goals that enables the brokers in an AAA broker team to start new brokers and recruit them to the broker team. As a result, an AAA-based multi-agent system can maintain a specified number of functional brokers in the system despite broker failures, thus effectively becoming a self-healing system.
15419677
STAPLE: An agent programming language based on the joint intention theory
Joint intention theory has been used for rule based creation of teams and to provide a formal semantics for communicative acts but there were no agent programming languages linked to this theory. We proposed a declarative agent programming language called STAPLE whose logical semantics is given by the joint intention theory. This paper illustrates the STAPLE support for communication and teamwork in a unified framework.
9907384
Integrating Joint Intention Theory, Belief Reasoning, and Communicative Action for Generating Team-Oriented Dialogue
The goal of this research is to develop an architecture that can guide an agent during collaborative teamwork. The architecture should generate communication and dialogue during the performance of collaborative multi-agent tasks as a byproduct of the agent's rationally pursuing its intentions. This paper describes how a joint intention interpreter that is integrated with a reasoner over beliefs and communicative acts can form the core of a dialogue engine. As an interpreter of joint actions, the architecture enables agent programmers to describe a domain declaratively, specifying an agent's individual and joint intentions, plans and actions at a high level. The interpreter attempts to fulfill the agent's individual and joint intentions, subject to its beliefs and mutual beliefs. As a consequence, the system engages in dialogue through the planning and execution of communicative acts necessary to attain the collaborative task at hand. The dialogue engine is general enough to be applicable to both agent-agent and agent-human teams. The system has been implemented in a combination of Java and Prolog, and can be shown to obey the predictions of joint intention.
17321819
Toward A Formalism for Conversation Protocols Using Joint Intention Theory
Conversation protocols are meant to achieve certain tasks or to bring about certain state of affairs in the world. Therefore, one may identify the landmarks or the state of affairs that must be brought about during the execution of a protocol in order to achieve its goal. Accordingly, the most important aspect of protocols is these landmarks rather than the communicative actions needed to achieve the landmarks. We show that families of conversation protocols can be expressed formally as partially ordered landmarks where each landmark is characterized by propositions that are true in the state represented by that landmark. Dialogue in natural languages is regarded as joint activity. Conversation protocols in multi-agent systems are treated as dialogue templates and are composed using speech acts from natural language dialogues. As such, we treat conversation protocols as joint action expressions and gainfully apply existing formal theories of dialogue, specifically the Joint Intention Theory, to protocols and their compositions. Conversation protocols may require agents to communicate with groups as well as individuals. However, most contemporary agent communication languages, notably FIPA and KQML, have either no provision or no well-defined semantics for group communication. Furthermore, the research on protocols so far does not correctlymore » incorporate groups into the protocols. We give a formal semantics to group communicative acts and use it to handle group communication in a formal treatment of protocols.« less
3185097
Towards a fault-tolerant multi-agent system architecture
Multi-agent systems are prone to failures typical of any distributed system. Agents and resources may become unavailable due to machine crashes, communication breakdowns, process failures, and numerous other hardware and software failures. Most of the work done in fault handling in multi-agent systems deals with detection and recovery from faults such as state-inconsistencies, relying on the traditional techniques for recovering from other distributed systems failure. However, the traditional fault-tolerance techniques are designed for specific situations and they require special infrastructural support. We argue for fault-tolerance techniques that can be readily implemented using a generic agent shell with minimal or no modification to the agent infrastructure. We propose that theories from multi-agent systems literature can be effectively combined with basic fault-tolerance principles to design robust multi-agent systems. In particular, we argue that (1) teamwork may be used to create a robust brokered architecture that can recover a multi-agent system from broker failures without incurring undue overheads, (2) teamwork may also be used to guarantee a specified number of brokers in a large multi-agent system, and (3) agent autonomy can be used to prevent thrashing and guarantee acceptable levels of quality of service by an agent. We also describe the Adaptive Agent Architecture (AAA), a fault-tolerant brokered multi-agent system architecture, and present experimental evidence using the AAA to validate our approach.
1631355
Threads Yield Continuations
Just as a traditional continuation represents the rest of acomputation from a given point in the computation, a subcontinuationrepresents the rest of a subcomputation from agiven point in the subcomputation. Subcontinuationsare more expressive than traditional continuations and have been shown to beuseful for controlling tree-structured concurrency, yet they havepreviously been implemented only on uniprocessors. This article describes aconcurrent implementation of one-shot subcontinuations. Like one-shotcontinuations, one-shot subcontinuations are first-class but may be invokedat most once, a restriction obeyed by nearly all programs that usecontinuations. The techniques used to implement one-shot subcontinuationsmay be applied directly to other one-shot continuation mechanisms and may begeneralized to support multi-shot continuations as well. A novel feature ofthe implementation is that continuations are implemented in terms ofthreads. Because the implementation model does not rely upon any speciallanguage features or compilation techniques, the model is applicable toany language or language implementation that supports a small set of threadprimitives.
1574370
Bounding blocking probabilities and throughput in queueing networks with buffer capacity constraints
We propose a new technique for upper and lower bounding of the throughput and blocking probabilities in queueing networks with buffer capacity constraints, i.e., some buffers in the network have finite capacity. By studying the evolution of multinomials of the state of the system in its assumed steady state, we obtain constraints on the possible behavior of the system. Using these constraints, we obtain linear programs whose values upper and lower bound the performance measures of interest, namely throughputs or blocking probabilities. The main advantages of this new technique are that the computational complexity does not increase with the size of the finite buffers and that the technique is applicable to systems in which some buffers have infinite capacity. The technique is demonstrated on examples taken from both manufacturing systems and communication networks. As a special case, for the M/M/s/s queue, we establish the asymptotic exactness of the bounds, i.e., that the bounds on the blocking probability asymptotically approach the exact value as the degree of the multinomials considered is increased to infinity.
1061170
Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations
BackgroundModern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns.ResultsThe effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches.ConclusionsWe conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns.
7470034
Recognition of human actions using moment based features and artificial neural networks
This paper presents performance of view-based approach in automated recognition of predefined hand and gross body actions using artificial neural network. This approach represents motion by a static grey scale image template computed by collapsing the temporal components into the cumulative image-difference of frames. The seven invariant Hu moments are used as the feature vectors. The performance of the system is tested in real time using feed forward multilayer perceptron (MLP) based on back propagation.
7469370
Carbon: architectural support for fine-grained parallelism on chip multiprocessors
Chip multiprocessors (CMPs) are now commonplace, and the number of cores on a CMP is likely to grow steadily. However, in order to harness the additional compute resources of a CMP, applications must expose their thread-level parallelism to the hardware. One common approach to doing this is to decompose a program into parallel "tasks" and allow an underlying software layer to schedule these tasks to different threads. Software task scheduling can provide good parallel performance as long as tasks are large compared to the software overheads.
 We examine a set of applications from an important emerging domain: Recognition, Mining, and Synthesis (RMS). Many RMS applications are compute-intensive and have abundant thread-level parallelism, and are therefore good targets for running on a CMP. However, a significant number have small tasks for which software task schedulers achieve only limited parallel speedups.
 We propose Carbon, a hardware technique to accelerate dynamic task scheduling on scalable CMPs. Carbon has relatively simple hardware, most of which can be placed far from the cores. We compare Carbon to some highly tuned software task schedulers for a set of RMS benchmarks with small tasks. Carbon delivers significant performance improvements over the best software scheduler: on average for 64 cores, 68% faster on a set of loop-parallel benchmarks, and 109% faster on aset of task-parallel benchmarks.