Multi-threaded Communicating Agents in Qu-Prolog

In this tutorial paper we summarise the key features of the multi-threaded Qu-Prolog language for implementing multi-threaded communicating agent applications. Internal threads of an agent communicate using the shared dynamic database used as a generalisation of Linda tuple store. Threads in different agents, perhaps on different hosts, communicate using either a thread-to-thread store and forward communication system, or by a publish and subscribe mechanism in which messages are routed to their destinations based on content test subscriptions. We illustrate the features using an auction house application. This is fully distributed with multiple auctioneers and bidders which participate in simultaneous auctions. The application makes essential use of the three forms of inter-thread communication of Qu-Prolog. The agent bidding behaviour is specified graphically as a finite state automaton and its implementation is essentially the execution of its state transition function. The paper assumes familiarity with Prolog and the basic concepts of multi-agent systems.

Achieving cooperation in a distributed multi-robot team

DMAPS (Distributed Multi-Agent Planning System) is a planning system developed for distributed multi-robot teams based on MAPS(Multi-Agent Planning System). MAPS assumes that each agent has the same global view of the environment in order to determine the most suitable actions. This assumption fails when perception is local to the agents: each agent has only a partial and unique view of the environment. DMAPS addresses this problem by creating a probabilistic global view on each agent by fusing the perceptual information from each robot. The experimental results on consuming tasks show that while the probabilistic global view is not identical on each robot, the shared view is still effective in increasing performance of the team.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup)

Belief revision for adaptive negotiation agents

Existing negotiation agents are primitive in terms of what they can learn and how responsive they are towards the changing negotiation contexts. These weaknesses can be alleviated if an expressive representation language is used to represent negotiation contexts and a sound inference mechanism is applied to reason about the preferential changes arising in these negotiation contexts. This paper illustrates a novel adaptive negotiation agent model, which is underpinned by the well-known AGM belief revision logic. Our preliminary experiments show that the performance of the belief-based adaptive negotiation agents is promising.

Classifying an opponent's behaviour in robot soccer

This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observableenvironment, namely RoboCup small size league robot soccer. The performance is illustrated in the context of the highly successful robot soccer team, the RoboRoos. The project is broken into three tasks; classification of behaviours, modelling and prediction of behaviours and integration of the predictions into the existing planning system. A probabilistic approach is taken to dealing with the uncertainty in the observations and with representing the uncertainty in the prediction of the behaviours. Results are shown for a classification system using a Naïve Bayesian Network that determines the opponent’s current behaviour. These results are compared to an expert designed fuzzy behaviour classification system. The paper illustrates how the modelling system will use the information from behaviour classification to produce probability distributions that model the manner with which the opponents perform their behaviours. These probability distributions are show to match well with the existing multi-agent planning system (MAPS) that forms the core of the RoboRoos system.

Reflective web interface agent

Web interface agent is used with web browsers to assist users in searching and interactions with the WWW. It is used for a variety of purposes, such as web-enabled remote control, web interactive visualization, and e-commerce activities. User may be aware or unaware of its existence. The intelligence of interface agent consists in its capability of learning and decision-making in performing interactive functions on behalf of a user. However, since web is an open system environment, the reasoning mechanism in an agent should be able to adapt changes and make decisions on exceptional situations, and therefore use meta knowledge. This paper proposes a framework of Reflective Web Interface Agent (RWIA) that is to provide causal connections between the application interfaces and the knowledge model of the interface agent. A prototype is also implemented for the purpose of demonstration.

Inflatable rescue boat-related injuries in Queensland surf lifesavers: The epidemiology - biomechanics interface

The objective was to describe the relationship between epidemiological and biomechanical factors in the causal pathway of inflatable rescue boat (IRB)-related injuries in Australian surf lifesavers; to develop epidemiological and biomechanical methodologies and measurement instruments that identify and measure the risk factors, for use in future epidemiological studies. Epidemiological and biomechanical models of injury causation were combined. Host, agent and environmental factors that influenced total available force for transfer to host were specified. Measurement instruments for each of the specified risk factors were developed. Instruments were piloted in a volunteer sample of surf lifesavers. Participant characteristics were recorded using demographic questionnaires; IRB operating techniques were recorded using a custom-made on-board camera (Grand RF-Guard) and images of operating techniques were coded by two independent observers. Ground reaction forces transmitted to the host through the lifesaver's feet at the time of wave impact were measured using a custom-built piezoelectric force platform. The demographic questionnaire was found practical; the on-board camera functioned successfully within the target environment. Agreement between independent coders of IRB operating technique images was significant (p < 0.001) with Kappa values ranging from 0.5 to 0.7. Biomechanical instruments performed successfully in the target environment. Peak biomechanical forces were 415.6N (left foot) and 252.9N (right foot). This study defines the relationship between epidemiological and biomechanical factors in modifying the risk of IRB-related injury in a population of surf lifesavers. Preliminary feasibility of combining epidemiological and biomechanical information has been demonstrated. Further testing of the proposed model and measurement instruments is required.

Reversible active switching of the mechanical properties of a peptide film at a fluid-fluid interface

Designer peptides have recently been developed as building blocks for novel self-assembled materials with stimuli-responsive properties. To date, such materials have been based on self-assembly in bulk aqueous solution or at solid-fluid interfaces. We have designed a 21-residue peptide, AM1, as a stimuli-responsive surfactant that switches molecular architectures at a fluid-fluid interface in response to changes in bulk aqueous solution composition. In the presence of divalent zinc at neutral pH, the peptide forms a mechanically strong 'film state'. In the absence of metal ions or at acid pH, the peptide adsorbs to form a mobile 'detergent state'. The two interfacial states can be actively and reversibly switched. Switching between the two states by a change in pH or the addition of a chelating agent leads to rapid emulsion coalescence or foam collapse. This work introduces a new class of surfactants that offer an environmentally friendly approach to control the stability of interfaces in foams, emulsions and fluid-fluid interfaces more generally.