The University of Southampton

Dr. Long Tran-Thanh

Academic Staff

Personal homepage

I'm a lecturer (Assist. Prof. equivalent) in Computer Science.


  • AAAI 2012 Outstanding Paper Award, honourable mention

  • ECAI 2012 Best Student Paper Award, runner-up

  • ECCAI Artificial Intelligence Dissertation Award (for the best European PhD thesis in Artificial Intelligence in 2012), honourable mention

  • CPHC/BCS PhD Dissertation Award (for the best Computer Science PhD thesis in the UK in 2012/2013), runner-up


Research interests

 Sequential decision making

My primal research area is sequential decision making with constraints. More precisely, I am interested in multi-armed bandit (MAB) models where pulling an arm (i.e., making a decision) requires a cost and the total spending is limited by a finite budget. To tackle this problem, I have introduced a new model, called the budget-limited MAB, and have also proposed a number of arm pulling algorithms for which I have provided both theoretical and empirical performance analyses. I am also interested in applying this bandit model (or its variances) to other domains of AI, such as  (i) decentralised controlling for UAVs; (ii) information collection in wireless sensor networks; and (iii) budget-limited online keyword bidding.


Game theory

I mainly focus on large coalition formation games from both game theoretical and decision making perspective. In more detail, I look at systems where the number of participants is very large (typically thousands or more). Within these systems, calculating different solution concepts (e.g., the core, nucleolus, Shapley-value, etc.) are very hard. Given this, my goal is to identify approximation techniques that can efficiently provide high quality results. To do so, with some of my colleagues, we have introduced a novel, vector-based, representation model of the participating agents, with which we can calculate the abovementioned concepts in a significantly more efficient way. We have also analysed the error bounds of approximating the Shapley value in large games.


Staying within game theory, I also study different games with resource allocation from both aspects of classical and behaviourial game theory. In particular, I am interested in calculating different equilibria and price of anarchy. A preliminary version of work has been published at SAGT 2011. 


From the behaviourial game theory perspective, I aim to identify players' favourite strategies when they repeatedly play such games against different opponents (Repeated Colonel Blotto).



More recently, I investigate the performance of different crowdsourcing systems from a theoretical perspective, aiming to provide rigorous performance guarantees for task allocation algorithms. 


Home energy management

I am heavily involved in the research work on home energy management. In particular, we aim to improve the energy consumption profile of home owners, in order to reduce the CO2 emission of the domestic energy sector. To do so, as the first step, we mainly focussed on the accurate learning and prediction of homeowners' habit, such as appliance usage and heating preferences. 


Other research interests

The cost of interference to closed evolving systems: We investigate what is the cost to interfere into closed systems, if we want the system to achieve some desirable states. As a first step, we look at evolving evolutionary games, where an external decision maker can invest his resources into the system (e.g., via a reward scheme) such that in the long term, the agents will follow a preferred behaviour. A preliminary result has been presented at COIN 2014 and NAG 2014.


Stochastic shortest path problems: This is an ongoing work on approximating the classical stochastic shortest path, defined by Frank (1969). In particular, so far I have developed a new concentration inequality that provides a lower bound on the probability mass on the probability P(X < a) with a < E[X]. Combining this new result with other existing concentration bounds, I could provide a O(n^3) running time algorithm that can achieve O(1/n) approximation for sure (where n is the number of vertices). In addition, the algorithm works for any type of bounded distribution. To the best of my knowledge (which can be obsolete), the current state of the art is pseudo-polynomial with 2/n approximation coefficient, which only works on discrete distributions. Currently I am aiming to improve the approximation coefficient of my algorithm.


Non-monetary referral incentives: I am also investigating how non-monetary referral incentivisation work in social networks. You can find a preliminary version of our work here. For more details, you can visit the website of our project, or watch a video about it. 


EPSRC-Singapore funded project on cyber security for smart traffic control systems (£500K for 2 years): 2016 - 2018


Professional activities

Current activities:

I am a PC member of IJCAI 2016

I am a co-organiser of SecMAS at AAMAS 2016
Past activities:

I was a PC member of AAMAS (2012-2014), AAAI (2014), IJCAI (2013), EC (2013), WCNC (2013) and several other workshops (OPTMAS, CoopMAS, etc...) in the last few years

I was a reviewer for AAMAS (2010-2011), ICML (2012-2014), NIPS (2012-2014), COLT (2012-2013), SAGT (2012), PRIMA (2013), Artificial Intelligence, Journal of Machine Learning Research, Theoretical Computer Science, Swarm Intelligence

I was a co-organiser/chair of the HAIDM workshop series.

I was a co-organiser and chair of the MassiveMAS workshop at AAMAS 2015

Conferences attended

AAAI 2010 (Atlanta), 2012 (Toronto), 2015 (Austin) 

AAMAS 2009 (Budapest), 2012 (Valencia), 2013 (St. Paul), 2014 (Paris), 2015 (Istanbul)

COLT 2011 (Budapest)*,

EC (2012)*,

ECAI 2012 (Montpellier),

ICC 2010 (Cape Town), 

ICML 2012 (Edinburgh)*, 2015 (Lille)

IFORS 2008 (Sandton), 

IJCAI 2013 (Beijing), 2015 (Buenos Aires)

NIPS 2015 (Montreal)

SAGT 2011 (Amalfi), 

UAI 2014 (Quebec city),

WCNC 2009 (Budapest), 2010 (Sydney)

*: no paper presentations


I am organising the AIC seminar series. If you are interested in giving a talk in Southampton in artificial intelligence, machine learning, or game theory related topics, please let me know.

I am also running the AIC reading group series, where we come together to discuss topics that we are interested in. Further details will be uploaded later.


Kho, Johnsen, Tran-Thanh, Long, Rogers, Alex and Jennings, Nick (2009) Distributed Adaptive Sampling, Forwarding, and Routing Algorithms for Wireless Visual Sensor Networks At Third International Workshop on Agent Technology for Sensor Networks, a workshop of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-09), Hungary. 10 - 15 May 2009. , pp. 63-70.

Kho, Johnsen, Tran-Thanh, Long, Rogers, Alex and Jennings, Nicholas R. (2010) An Agent-Based Distributed Coordination Mechanism for Wireless Visual Sensor Nodes Using Dynamic Programming The Computer Journal, 53, (8), pp. 1277-1290.

Tran-Thanh, Long, Chapman, Archie, Munoz De Cote Flores Luna, Jose Enrique, Rogers, Alex and Jennings, Nicholas R. (2010) Epsilon–First Policies for Budget–Limited Multi-Armed Bandits At Twenty-Fourth AAAI Conference on Artificial Intelligence, Georgia. 11 - 15 Jul 2010. , pp. 1211-1216.

Tran-Thanh, Long (2010) Multi–Armed Bandit Models for Efficient Long–Term Information Collection in Wireless Sensor Networks s.n.

Tran-Thanh, Long, Rogers, Alex and Jennings, Nick (2012) Long–term information collection with energy harvesting wireless sensors: a multi–armed bandit based approach Autonomous Agents and Multi-Agent Systems, 25, (2), pp. 352-394. (doi:10.1007/s10458-011-9179-0).

Tran-Thanh, Long, Polukarov, Maria, Chapman, Archie, Rogers, Alex and Jennings, Nicholas R. (2011) On the Existence of Pure Strategy Nash Equilibria in Integer-Splittable Weighted Congestion Games At 4th International Symposium, SAGT 2011, Italy. , pp. 236-253. (doi:10.1007/978-3-642-24829-0_22).

Stranders, Ruben, Tran-Thanh, Long, Delle Fave, Francesco Maria, Rogers, Alex and Jennings, Nick (2012) DCOPS and bandits: Exploration and exploitation in decentralised coordination At Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Spain. , pp. 289-297.

Tran-Thanh, Long, Chapman, Archie, Rogers, Alex and Jennings, Nicholas R. (2012) Knapsack based optimal policies for budget-limited multi-armed bandits At Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), Canada. 22 Jul 2012. , pp. 1134-1140.

Tran-Thanh, Long (2012) Budget-limited multi-armed bandits University of Southampton, Faculty of Physical and Applied Sciences, Doctoral Thesis , 173pp.

Truong, Ngoc Cuong, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, Sarvapali D. (2012) Predicting energy consumption activities for home energy management At Agent Technologies for Energy Systems (ATES 2012), Spain. 8 pp.

Tran-Thanh, Long, Stein, Sebastian, Rogers, Alex and Jennings, Nicholas R. (2012) Efficient crowdsourcing of unknown experts using multi-armed bandits At 20th European Conference on Artificial Intelligence (ECAI 2012), France. 27 - 31 Aug 2012. , pp. 768-773. (doi:10.3233/978-1-61499-098-7-768).

Tran-Thanh, Long, Venanzi, Matteo, Rogers, Alex and Jennings, Nicholas R. (2013) Efficient Budget Allocation with Accuracy Guarantees for Crowdsourcing Classification Tasks At AAMAS '13 Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems. , pp. 901-908.

Tran-Thanh, Long, Nguyen, Tri-Dung, Rahwan, Talal, Rogers, Alex and Jennings, N. R. (2013) An efficient vector-based representation for coalitional games At IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence. , pp. 383-389.

Truong, Ngoc Cuong, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, D. Sarvapali (2013) Activity prediction for agent-based home energy management At Agent Technologies for Energy Systems (ATES 2013), United States. 06 - 07 May 2013. 8 pp.

Truong, Ngoc Cuong, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, Sarvapali D. (2013) Towards appliance usage prediction for home energy management At ACM E-Energy 2013, United States. 21 - 24 May 2013. 2 pp.

Truong, Ngoc Cuong, McInerney, James, Tran-Thanh, Long, Costanza, Enrico and Ramchurn, Sarvapali D. (2013) Forecasting multi-appliance usage for smart home energy management At 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), China. 03 - 09 Aug 2013.

Tran-Thanh, Long, Huynh, Trung Dong, Rosenfeld, A, Ramchurn, Sarvapali and Jennings, Nicholas R. (2014) BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees At 13th International Conference on Autonomous Agents and Multi-Agent Systems, France. 05 - 09 May 2014. , pp. 477-484.

Tran-Thanh, Long, Stein, Sebastian and Rogers, Alex et al. (2014) Efficient crowdsourcing of unknown experts using bounded multi-armed bandits Artificial Intelligence, 214, pp. 89-111.

Tran-Thanh, Long, Stavrogiannis, Lampros C., Naroditskiy, Victor, Robu, Valentin, Jennings, Nicholas R. and Key, Peter (2014) Efficient regret bounds for online bid optimisation in budget-limited sponsored search auctions At 30th Conference on Uncertainty in Artificial Intelligence, Canada. 23 - 27 Jul 2014. , pp. 809-818.

Han, TheAnh, Tran-Thanh, Long and Jennings, Nicholas R. (2014) The cost of interference in evolving systems At COIN 2014: The 17th International Workshop on Coordination, Organisations, Institutions and Norms, France. 06 Jun 2014.

Naroditskiy, Victor, Stein, Sebastian, Tonin, Mirco, Tran-Thanh, Long, Vlassopoulos, Michael and Jennings, N.R. (2014) Referral incentives in crowdfunding At HCOMP2014: Conference on Human Computation &amp; Crowdsourcing, United States. 02 - 04 Nov 2014. , pp. 171-183.

Tran-Thanh, Long, Huynh, Trung Dong, Rosenfeld, Avi, Ramchurn, Sarvapali D. and Jennings, Nicholas R. (2015) Crowdsourcing Complex Workflows under Budget Constraints At Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), United States. 25 - 30 Jan 2015. , pp. 1298-1304.

Tran-Thanh, Long, Xia, Yingce, Qin, Tao and Jennings, N. R. (2015) Efficient Algorithms with performance guarantees for the stochastic multiple-choice knapsack problem At IJCAI 2015, Argentina. , pp. 403-409.

Tran-Thanh, Long, Xu, Haifeng and Jennings, Nicholas R. (2016) Playing repeated security games with no prior knowledge At Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), Singapore. 09 - 13 May 2016. 9 pp.

Kawale, Jaya, Bui, Hung, Kveton, Branislav, Tran-Thanh, Long and Chawla, Sanjay (2015) Efficient Thompson sampling for online matrix-factorization recommendation At Neural Information Processing Systems (NIPS 2015), Canada. 07 - 12 Dec 2015. , pp. 1297-1305.

Truong, Ngoc Cuong, Baarslag, Tim, Ramchurn, Gopal and Tran-Thanh, Long (2016) Interactive scheduling of appliance usage in the home At 25th International Joint Conference on Artificial Intelligence (IJCAI-160, United States. 09 - 15 Jul 2016. 7 pp.

Waniek, Marcin, Tran-Thanh, Long, Michalak, Tomasz P. and Jennings, Nicholas (2017) The dollar auction with spiteful players In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence and the Twenty-Ninth Innovative Applications of Artificial Intelligence Conference. vol. 1, Association for the Advancement of Artificial Intelligence. 7 pp.

Guo, Qingyu, An, Bo and Tran-Thanh, Long (2017) Playing repeated network interdiction games with semi-bandit feedback In Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). 9 pp.

Zhang, Youzhi, An, Bo, Tran-Thanh, Long, Wang, Zhen, Gan, Jiarui and Jennings, Nicholas R. (2017) Optimal escape Interdiction on transportation networks At International Joint Conference on Artificial Intelligence, Melbourne, Australia. 19 - 25 Aug 2017. 9 pp.


Telephone: +442380593715


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