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55 results

Commonsense-enhanced Natural Language Generation for Human-Robot Interaction

Conference Proceeding
Gkatzia, D. (in press)
Commonsense-enhanced Natural Language Generation for Human-Robot Interaction
Commonsense is vital for human communication, as it allows us to make inferences without explicitly mentioning the context. Equipping robots with commonsense knowledge would l...

The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World

Conference Proceeding
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., …Tyrrell, A. M. (2019)
The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. In ALIFE 2019: The 2019 Conference on Artificial Life, 95-102. https://doi.org/10.1162/isal_a_00147
The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the ...

Evolving robust policies for community energy system management

Conference Proceeding
Cardoso, R., Hart, E., & Pitt, J. (2019)
Evolving robust policies for community energy system management. In GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference, (1120-1128). https://doi.org/10.1145/3321707.3321763
Community energy systems (CESs) are shared energy systems in which multiple communities generate and consume energy from renewable resources. At regular time intervals, each p...

Algorithm Selection Using Deep Learning

Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2019)
Algorithm Selection Using Deep Learning. In GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference, (198-206). https://doi.org/10.1145/3321707.3321845
We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In ...

Simulating Dynamic Vehicle Routing Problems with Athos

Conference Proceeding
Hoffman, B., Guckert, M., Chalmers, K., & Urquhart, N. (2019)
Simulating Dynamic Vehicle Routing Problems with Athos. In Proceedings of the 33rd International ECMS Conference on Modelling and Simulation ECMS 2019, (296-302). https://doi.org/10.7148/2019-0296
Complex routing problems, such as vehicle routing problems with additional constraints, are both hard to solve and hard to express in a form that is accessible to the human ex...

Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids

Conference Proceeding
Powers, S. T., Meanwell, O., & Cai, Z. (2019)
Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids. In PAAMS 2019: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection, 269-272. https://doi.org/10.1007/978-3-030-24209-1_28
Reducing peak electricity consumption is important to maximise use of renewable energy sources, and reduce the total amount of capacity required on a grid. Most approaches use...

Optimising Real-World Traffic Cycle Programs by Using Evolutionary Computation

Journal Article
Segredo, E., Luque, G., Segura, C., & Alba, E. (2019)
Optimising Real-World Traffic Cycle Programs by Using Evolutionary Computation. IEEE Access, 7, 43915-43932. https://doi.org/10.1109/ACCESS.2019.2908562
Traffic congestion, and the consequent loss of time, money, quality of life, and higher pollution, is currently one of the most important problems in cities, and several approa...

Simulating the actions of commuters using a multi-agent system

Journal Article
Urquhart, N., Powers, S., Wall, Z., Fonzone, A., Ge, J., & Polhill, G. (2019)
Simulating the actions of commuters using a multi-agent system. Journal of Artificial Societies and Social Simulation, 22(2), https://doi.org/10.18564/jasss.4007
The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is de...

Athos - A Model Driven Approach to Describe and Solve Optimisation Problems

Conference Proceeding
Hoffman, B., Chalmers, K., Urquhart, N., & Guckert, M. (2019)
Athos - A Model Driven Approach to Describe and Solve Optimisation Problems. https://doi.org/10.1145/3300111.3300114
Implementing solutions for optimisation problems with general purpose high-level programming languages is a time consuming task that can only be carried out by professional so...

A Cooperative Learning Approach for the Quadratic Knapsack Problem

Conference Proceeding
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018)
A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12), (31-35). https://doi.org/10.1007/978-3-030-05348-2_3
The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has sever...