Ing. Tatiana V. Guy, Ph.D. (external collaborator)
Rozvažování o cílech rozhodování
| advisor: |
Ing. Tatiana V. Guy, Ph.D. |
| e-mail: |
show e-mail
|
| type: |
phd thesis
|
| branch of study: |
MI_MM, MI_AMSM, MINF |
| description: |
Abstrakt: Dynamické přehodnocování cílů rozhodování. Penalizace změn cílů rozhodování závisící na ceně rozvažování nutného ke změně. Jak se vyrovnat se závislostmi mezi cíli rozhodování (zvláště rozpornými)? Jak upravit kritérium? Jak má být zohledněna cena dosažení dílčího cíle?
Title: Negotiation about DM goals: when does selfishness cost less?
Abstract: Dynamical reconsidering of DM goals. Penalisation of modification of DM goal in dependence on the deliberation cost of the change. How to cope with possible (inter-)dependency of DM goals (especially conflicting ones)? How to modify the criterion? How the cost of reaching the particular DM goal can be taken into account?
Description:
The distributed decision making (DM) arise when there is no possibility to govern in a centralised way. Any DM task of that type consider either several interacting, locally independent elements, which have their local goals, but have to collaborate to reach a common (group) goal (e.g.: cooperative robots, multi-agent systems, sensor networks); or a set of independent elements with own goals that need to coordinate their activities (e.g. vehicles in urban transportation). The success of a distributed solution depends on efficiency of cooperation. Even in the case when elements are independent they may benefit from the creation of a common DM goal - two are better than one because they can help each other succeed. If I respect my neighbour’s interests, I will reach my own DM goal with less energy. Otherwise, there is a danger the interacting elements will compete even without an explicit conflict of their DM goals.
However, any negotiation costs significant time and computation resources each of interacting elements.
Evaluation and optimising the tradeoff between the computational cost (time) of negotiation and a potential reward (given by a reached compromise between DM goals) should be an essential part of feasible normative DM theory. The PhD project will focus on the DM goal deliberation formulated and solved as a decision-making problem within the fully probabilistic framework [1]. The expected contribution should finally serve to normative Bayesian distributed DM under a flat cooperation structure.
The preliminary conceptual solution relies on a combination of the inductive memory-based technique [3] and fully probabilistic extension of Bayesian DM [1], [5].
The proposed topic of doctoral theses can be tailored to the specific PhD student, his/her skills and inclination to theoretical or algorithmic development possibly with emphasise placed on a specific application domain. |
| references: |
Literature
[1] Kárný M., Guy T.V.: Fully probabilistic control design. Systems & Control Letters, 55(4), 2006
[2] Kárný M., Kroupa T.: Axiomatisation of fully probabilistic design, Inf. Sciences,186, 1, 105-113, 2012
[3] Artificial Intelligence Review: Special Issue on Lazy Learning 11(1–5), 1–6, 1997.
[4] Guy T.V, Kárný M, Wolpert D.H. (Eds): Decision Making with Imperfect Decision Makers, Springer, vol. 28, 2012
[5] Kárný M .,Guy T.V, Bodini A, Ruggeri F.: Cooperation via sharing of probabilistic information, Int. J. of Computational Intelligence Studies, 1:2 139-162, 2009 |
| note: |
Good knowledge of English is essential. |
| last update: |
23.05.2018 14:57:34 |
Kooperace v distribuovaném rozhodování
| advisor: |
Ing. Tatiana V. Guy, Ph.D. |
| e-mail: |
show e-mail
|
| type: |
phd thesis
|
| branch of study: |
MI_MM, MI_AMSM, MINF |
| key words: |
cooperation, negotiation, coalition formation |
| description: |
Abstrakt:
Dynamické rozhodování v netriviálních situacích není realizovatelné jedním agentem. Distribuované
řešeni vyžaduje řešení kooperačních úloh. Tématem práce je teoreticko-algoritmická podpora kooperace.
Title: Cooperation in distributed decision making.
Abstract: Independently performing decision makers should be able to coordinate distribution of their deliberation efforts (scenario when a decision maker stops thinking while other needs to continue deliberation may lead to poor behaviour of both). Moreover, competitive scenario with several decision makers requires ability of each to monitor deliberation process of his neighbours under little knowledge about them.
Description:
In a very general formulation, dynamic decision making (DDM) could be regarded as the design and coordination of interconnected decisions distributed over a variety of decision makers, either treating some problem of mutual interest or acting within a common environment. Elements of structures emerging in economy and management are examples of agents acting within DDM. Indeed, the vertically integrated organisation structures used in management and economics (e.g., multi-stage production, insurance, investment) have been recently replaced by an ensemble of stand-alone components, which are interconnected via exchange of goods/services/money. The novel organisation structure represents a network system with a variable structure. Thus, the relative performance of the individual network’s components (agents) and interactions between them fully determine the global behaviour of the whole network.
The proposed project aims to contribute to theoretical and algorithmic development of cooperation and negotiation aspects while respecting agent imperfection and deliberation. The solution should be applicable to decentralised dynamic DM under complexity and uncertainty. A flat cooperation structure without pre-coordination is considered. The aim of this PhD project is: i) define the cooperation patterns that suit the project objective. ii) formulate basic cooperation and negotiation rules and requirements on the cooperation structure; iii) the theoretical framework of cooperation and negotiation potentially applicable in decentralised DM; iv) Verification of expected properties of the proposed cooperation structures.
The proposed topic of doctoral theses can be tailored to the specific PhD student, his/her skills and inclination to theoretical or algorithmic development possibly with emphasise placed on a specific application domain. |
| references: |
Literature:
[1] J. C. Harsanyi, Games with Incomplete Information Played by \"Bayesian\" Players, I-III. Part I. The Basic Model Management Science Vol. 14, No. 3, Theory Series, 1967
[2] D. H.Wolpert, J. Grana, B. Tracey, T. Kohler, A. Kolchinsky, Modeling Social Organizations as Communication Networks arXiv preprint arXiv:1702.04449, 2017.
[3] M.Kárný, T.V.Guy, A.Bodini, F.Ruggeri, Cooperation via sharing of probabilistic information, International Journal of Computational Intelligence Studies, p. 139-162, 2009 |
| note: |
Good knowledge of English is essential. |
| last update: |
23.05.2018 16:58:44 |
Probabilistic modelling opinion formation in social interactions
| advisor: |
Ing. Tatiana V. Guy, Ph.D. |
| e-mail: |
show e-mail
|
| type: |
phd thesis
|
| branch of study: |
MI_MM, MI_AMSM, MINF, APIN |
| key words: |
opinion formation; decision making; social interactions. |
| description: |
The social networks and online media irreversibly changed the way we become informed, and form our opinions [1]. Social networks are not organised via centralised decision making but through complex chain-like processes, where news items spread over different groups of members. Thus we observe a new phenomenon when agents (both humans and artificial ones) evaluate alternative opinions based on the opinions/judgements obtained from others (followers, friends, collaborators, etc.). High support of the favoured opinion in the social interaction is taken as a positive feedback that reinforces the value associated with this opinion.
This phenomenon together with the constantly growing amount of circulating information catalyse different social effects: i) social exclusion and distrust [2]; ii) tendency to mimic the behaviour of other members [3]. In particular, echo chambers [2] quantified across different social networks have raised significant concerns on their potential impact on the spread of misinformation and on the overall behaviour of the social network.
The proposed topic of PhD project aims at modelling opinion formation in social interactions by means of probabilistic modelling agents’ opinions as well as reinforcement mechanisms driving opinion change. Besides mostly theoretical insights into opinion formation process, the intended research could provide a solution how to stimulate transition from individual opinion to a consensus. |
| references: |
The literature will be gradually added based on the progress achieved.
[1] Quattrociocchi W, Caldarelli G, Scala A. Opinion dynamics on interacting networks: media competition and social influence. Scientific reports. 2014; 4:4938. https://doi.org/10.1038/srep04938
[2] Nguyen, C., Echo chambers and epistemic bubbles, Episteme, 17(2), 2020.
[3] Garcia, D. et al, Social resilience in online communities: The autopsy of friendster. Proc. COSN\'13, 2013.
[4] Hahn, U. et al, How good is your evidence & how would you know? Top Cogn Sci, 10(4), 6, 2018. [5] M. H. DeGroot Optimal Statistical Decisions, Wiley 2004 |
| last update: |
25.09.2020 18:42:12 |
V3S Database
The application records results of science and research, and other academic activities. The V3S application serves as a tool for submitting data to the RIV database, exporting data for statistic analyses, and internal evaluation of research.
List of publications in V3S
administrator for this page:
Radek Fučík | last update: 08/07/2011
