Chatterbox challenge as a test-bed for synthetic emotions

Chatterbox Challenge is an annual web-based contest for artificial conversational systems, ACE. The 2010 instantiation was the tenth consecutive contest held between March and June in the 60th year following the publication of Alan Turing’s influential disquisition ‘computing machinery and intelligence’. Loosely based on Turing’s viva voca interrogator-hidden witness imitation game, a thought experiment to ascertain a machine’s capacity to respond satisfactorily to unrestricted questions, the contest provides a platform for technology comparison and evaluation. This paper provides an insight into emotion content in the entries since the 2005 Chatterbox Challenge. The authors find that synthetic textual systems, none of which are backed by academic or industry funding, are, on the whole and more than half a century since Weizenbaum’s natural language understanding experiment, little further than Eliza in terms of expressing emotion in dialogue. This may be a failure on the part of the academic AI community for ignoring the Turing test as an engineering challenge.

Exploring carrier agents in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? The work reported in this paper is motivated towards bridging this gap by proposing a swarm-array computing approach based on ‘Intelligent Agents’ to achieve autonomy for distributed parallel computing systems. In the proposed approach, a task to be executed on parallel computing cores is carried onto a computing core by carrier agents that can seamlessly transfer between processing cores in the event of a predicted failure. The cognitive capabilities of the carrier agents on a parallel processing core serves in achieving the self-ware objectives of autonomic computing, hence applying autonomic computing concepts for the benefit of parallel computing systems. The feasibility of the proposed approach is validated by simulation studies using a multi-agent simulator on an FPGA (Field-Programmable Gate Array) and experimental studies using MPI (Message Passing Interface) on a computer cluster. Preliminary results confirm that applying autonomic computing principles to parallel computing systems is beneficial.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Acceleration of radio network optimisation algorithms

The increasing demand for cheaper-faster-better services anytime and anywhere has made radio network optimisation much more complex than ever before. In order to dynamically optimise the serving network, Dynamic Network Optimisation (DNO), is proposed as the ultimate solution and future trend. The realization of DNO, however, has been hindered by a significant bottleneck of the optimisation speed as the network complexity grows. This paper presents a multi-threaded parallel solution to accelerate complicated proprietary network optimisation algorithms, under a rigid condition of numerical consistency. ariesoACP product from Arieso Ltd serves as the platform for parallelisation. This parallel solution has been benchmarked and results exhibit a high scalability and a run-time reduction by 11% to 42% based on the technology, subscriber density and blocking rate of a given network in comparison with the original version. Further, it is highly essential that the parallel version produces equivalent optimisation quality in terms of identical optimisation outputs.

Hardware development of the Yorick series of active vision systems

This paper presents a review of the design and development of the Yorick series of active stereo camera platforms and their integration into real-time closed loop active vision systems, whose applications span surveillance, navigation of autonomously guided vehicles (AGVs), and inspection tasks for teleoperation, including immersive visual telepresence. The mechatronic approach adopted for the design of the first system, including head/eye platform, local controller, vision engine, gaze controller and system integration, proved to be very successful. The design team comprised researchers with experience in parallel computing, robot control, mechanical design and machine vision. The success of the project has generated sufficient interest to sanction a number of revisions of the original head design, including the design of a lightweight compact head for use on a robot arm, and the further development of a robot head to look specifically at increasing visual resolution for visual telepresence. The controller and vision processing engines have also been upgraded, to include the control of robot heads on mobile platforms and control of vergence through tracking of an operator's eye movement. This paper details the hardware development of the different active vision/telepresence systems.

A modular head/eye platform for real-time reactive vision

This paper describes the design, implementation and testing of a high speed controlled stereo “head/eye” platform which facilitates the rapid redirection of gaze in response to visual input. It details the mechanical device, which is based around geared DC motors, and describes hardware aspects of the controller and vision system, which are implemented on a reconfigurable network of general purpose parallel processors. The servo-controller is described in detail and higher level gaze and vision constructs outlined. The paper gives performance figures gained both from mechanical tests on the platform alone, and from closed loop tests on the entire system using visual feedback from a feature detector.

A cluster computing implementation of a Monte Carlo simulation of a particle growth mechanism

Clusters of computers can be used together to provide a powerful computing resource. Large Monte Carlo simulations, such as those used to model particle growth, are computationally intensive and take considerable time to execute on conventional workstations. By spreading the work of the simulation across a cluster of computers, the elapsed execution time can be greatly reduced. Thus a user has apparently the performance of a supercomputer by using the spare cycles on other workstations.