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Updated by Konstantin Vikhorev on 12/03/2013.

Contact Details:
Dr. Konstantin Vikhorev
The Virtual Engineering Centre  
University of Liverpool
STFC Daresbury Laboratory
Daresbury Science and Innovation Campus
Warrington, WA4 4AD
United Kingdom
Phone: +44 (0) 1925 864-851
Konstantin Vikhorev's Home Page

University of Liverpool GAMMA Programme Virtual Engineering Centre

I am currently a Research Associate at the Virtual Engineering Centre (VEC), University of Liverpool. I am working on The Growing Autonomous Mission Management Applications (GAMMA) programme. GAMMA is a three year £9.1 million, Autonomous Systems programme aimed at driving SME engagement and developing technology within the emerging autonomous systems markets.

I was a Research Engineer at the Institute of Energy and Sustainable Development (IESD), De Montfort University. I was working on the Knowledge Awareness Prediction of man, machine and method in manufacturing (KAP) project for 2.5 years. KAP is a €12.8 M project co-financed by the European Commission under theme ICT-2010.10.1 ICT for agile and environmentally friendly manufacturing. The KAP research project aims to provide manufacturing standards to ensure that every existing resource can be used as efficiently as possible through the effective coordination of man, machine, material, and method. During this time I was module leader for Dynamics and Control at the Faculty of Technology, De Montfort University.

I obtained my PhD at the School of Computer Science, University of Nottingham in 2011. I worked on the project “Real-time guarantees in high-level agent programming languages project”. The project explored ways of adding real-time guarantees to Belief-Desire-Intentions agents. I completed my MSc in Mechatronics at De Montfort University in September 2007 and Dipl.-Ing in Automatic Control Systems at Bauman Moscow State Technical University in July of 2006.

My research interests include unmanned aircraft system (UAS), agent-based systems, and energy efficiency. In particular, I am focusing on providing information solutions for autonomous control and optimisation. I have also published around 20 refereed journal and conference papers.

ESTA 2011: Energy Services and Technology Association Workshop
MALLOW 2009: Multi-Agent Logics, Languages, and Organisations Federated Workshops
EASSS 2009: The European Agent Systems Summer School 2008
EASSS 2008: The European Agent Systems Summer School 2008
ICNPAA 2007: Mathematical Problems in Engineering,  Aerospace and Sciences

As part of my work I was developing a software framework for advanced industrial energy management. It allows continuously obtaining energy-related information from any location of interest at the factory floor and combining this data with enterprise wide information to enable system-wide optimization. The framework includes the features of today’s energy management systems with the addition of metrics to promote energy awareness in the context of productivity. The framework also incorporates energy data standards to mitigate the inconsistency and unreliability of much current practice with respect to energy data. Techniques like complex event processing (CEP) and data stream analysis algorithms allow computing key performance indicators on-the-fly to provide real-time monitoring. The CEP engine also provides real-time decision support (DS) information for increasing energy efficiency and diagnosing failures at the production process level. This allows the workforce to be more energy aware and to make energy efficient decisions.

The framework has been deployed via a prototype information system in a VOLVO Trucks machining line, Skövde plant, Sweden It allows the workforce to be more energy aware and to make energy efficient decisions. Results of this research were published in international refereed journals.

In the similar way the proposed approach can be used to automatically detect unnecessary energy usage and provide real-time decision support to building energy managers allowing them to improve energy efficiency, reduce carbon emissions, and manage financial risk.

Real-Time Agent Programming Systems


AgentSpeak(RT): Agent System with deadlines and priorities

AgentSpeak(RT) is a real-time BDI agent programming language based on AgentSpeak(L). AgentSpeak(RT) extends AgentSpeak intentions with deadlines which specify the time by which the agent should respond to an event, and priorities which specify the relative importance of responding to a particular event. The AgentSpeak(RT) interpreter commits to a priority-maximal set of intentions: a set of intentions which is maximally feasible while preferring higher priority intentions. We prove some properties of the language, such as guaranteed reactivity delay of the AgentSpeak(RT) interpreter and probabilistic guarantees of successful execution of intentions by their deadlines.

ARTS: Agent Real-Time System

ARTS, an implementation of the real-time BDI agent architecture. ARTS is an agent programming framework for agents with soft real-time guarantees; an ARTS agent will attempt to achieve as many high priority tasks by their specified deadlines as possible. The syntax and execution semantics of ARTS is based that of PRS-CL and JAM, augmented with information about deadlines, priorities, and durations, and changes to the interpreter to implement time bounded priority driven plan selection and deadline monotonic intention scheduling. ARTS is implemented in Java, and the current prototype implementation includes the core language described below, and implementations of some basic primitive actions. Additional user-defined primitive actions can be added using a Java API.

An ARTS agent consists of five main components: a database, a goal stack, a plan library, an intention structure, and an interpreter. Changes to the agent's environment or posting of new goals invokes reasoning to search for plans that might be applied to the current situation. The ARTS interpreter selects one plan from the list of applicable plans, schedules it, and executes a step of the most urgent intention in the computed schedule.