Maria Polukarov

JAAMAS Journal 2026 Journal Article

Green disclosure policies and market dynamics: evidence from agent-based ESG models

• Lingxiao Zhao
• Maria Polukarov
• Carmine Ventre

Abstract Green disclosure policies aim to improve the transparency of corporate environmental practices and guide investors’ capital allocation. While existing studies mostly examine firm-level effects, their market-level implications in multi-agent systems remain insufficiently explored. This paper develops a dual-market dynamic ESG fund model, integrating agent-based simulation with empirical game-theoretic analysis, to study how upgrade costs, investor valuation preferences, and disclosure regimes jointly shape firms’ green transition incentives in the EU and China. The results show that both transition costs and valuation gaps strongly influence strategic upgrading behaviour and equilibrium outcomes: Strict disclosure sharpens differentiation but may suppress upgrading due to high costs; lax disclosure facilitates initial transitions by polluting firms; and hybrid disclosure, combining lax and strict phases, generates stronger incentives across different firm types. Cross-market comparison further indicates that the EU’s mature regulatory environment is better suited to strict disclosure, whereas China’s emerging market benefits more from a lax form to accelerate early-stage transitions. This study provides a reference for regulators in selecting appropriate disclosure forms at different levels of market maturity and offers methodological support for the sustainable development of green finance markets.

AAMAS Conference 2025 Conference Paper

Agent-Based Analysis of Green Disclosure Policies and Their Market-Wide Impact on Firm Behavior

• Lingxiao Zhao
• Maria Polukarov
• Carmine Ventre

Green disclosure policies are designed to help firms communicate their environmentally friendly practices to investors. While most research has focused on the effects of these policies at the individual firm level, their influence within a system of multiple firms remains largely unexamined. To address this gap, we develop an agent-based model to simulate market dynamics among firms with varying levels of environmental performance and strategic responses. Using Empirical Game-Theoretic Analysis, we investigate how the costs associated with becoming greener and investors’ valuation of these efforts shape equilibrium outcomes and the prevalence of green firms in the market. Our findings reveal that changes in the cost of green upgrades significantly influence firms’ strategic choices and alter the equilibrium behavior of the other firms. Additionally, we analyze the effects of different green disclosure policies and find that under more relaxed policies, firms are more willing to incur into higher upgrade costs. Furthermore, we propose a two-stage disclosure policy that incentivizes all types of firms to improve their green practices, leading to broader adoption of sustainable energy solutions across the market.

ECAI Conference 2025 Conference Paper

Optimal Candidate Positioning in Multi-Issue Elections

• Colin Cleveland
• Bart de Keijzer
• Maria Polukarov

We study strategic candidate positioning in multidimensional spatial-voting elections. Voters and candidates are represented as points in Rd and each voter supports the candidate that is closest under a distance induced by an ℓp-norm. We prove that computing an optimal location for a new candidate is NP-hard already against a single opponent, whereas for a constant number of issues the problem is tractable: an O(nd + 1) hyperplane-enumeration algorithm and an O(n log n) radial-sweep routine for d = 2 solve the task exactly. We further derive the first approximation guarantees for the general multi-candidate case and show how our geometric approach extends seamlessly to positional scoring rules such as k-approval and Borda. These results clarify the algorithmic landscape of multi-dimensional spatial elections and provide practically implementable tools for campaign strategy.

AAMAS Conference 2023 Conference Paper

Error in the Euclidean Preference Model

• Luke Thorburn
• Maria Polukarov
• Carmine Ventre

Spatial models of preference, in the form of vector embeddings, are learned by many deep learning and multiagent systems, including recommender systems. Often these models are assumed to approximate a Euclidean structure, where an individual prefers alternatives positioned closer to their “ideal point”, as measured by the Euclidean metric. However, Bogomolnaia and Laslier [3] showed that there exist ordinal preference profiles that cannot be represented with this structure if the Euclidean space has two fewer dimensions than there are individuals or alternatives. We extend this result, showing that there are realistic situations in which almost all preference profiles cannot be represented with the Euclidean model, and derive a theoretical lower bound on the expected error when using the Euclidean model to approximate non-Euclidean preference profiles. Our results have implications for the interpretation and use of vector embeddings, because in some cases close approximation of arbitrary, true ordinal relationships can be expected only if the dimensionality of the embeddings is a substantial fraction of the number of entities represented.

IJCAI Conference 2023 Conference Paper

Error in the Euclidean Preference Model

• Luke Thorburn
• Maria Polukarov
• Carmine Ventre

Spatial models of preference, in the form of vector embeddings, are learned by many deep learning and multiagent systems, including recommender systems. Often these models are assumed to approximate a Euclidean structure, where an individual prefers alternatives positioned closer to their "ideal point", as measured by the Euclidean metric. However, previous work has shown there are ordinal preference profiles that cannot be represented with this structure if the Euclidean space has two fewer dimensions than there are individuals or alternatives. We extend this result, showing that there are situations in which almost all preference profiles cannot be represented with the Euclidean model, and derive a theoretical lower bound on the expected error when using the Euclidean model to approximate non-Euclidean preference profiles. Our results have implications for the interpretation and use of vector embeddings, because in some cases close approximation of arbitrary, true ordinal relationships can be expected only if the dimensionality of the embeddings is a substantial fraction of the number of entities represented.

AAMAS Conference 2022 Conference Paper

The Spoofing Resistance of Frequent Call Markets

• Buhong Liu
• Maria Polukarov
• Carmine Ventre
• Lingbo Li
• Leslie Kanthan
• Fan Wu
• Michail Basios

We study the effects of spoofing attacks on frequent call markets (FCMs). Spoofing—a strategic manipulation to mislead market participants by creating spurious limit orders—could harm the market efficiency and has been declared illegal in many countries. However, this practice is still very common, which inspired extensive research on measuring, detecting and curbing such manipulation in the popular market model of continuous double auctions (CDAs). In this paper, we extend this research to frequent call markets and use agent-based modelling to simulate spoofing in this context. Specifically, we apply empirical game-theoretic analysis (EGTA) to compute equilibria of agent-based markets, and demonstrate that while spoofing may be profitable in both market models, it has less impact on FCMs as opposed to CDAs. Finally, we explore several FCM mechanism designs to help to curb this type of market manipulation even further.

AAMAS Conference 2021 Conference Paper

Call Markets with Adaptive Clearing Intervals

• Buhong Liu
• Maria Polukarov
• Carmine Ventre
• Lingbo Li
• Leslie Kanthan

Trading mechanisms play a fundamental role in the health of financial markets. For example, it is believed that continuous double auctions constitute fertile soil for predatory behaviour and toxic order flows. To this end, frequent call markets have been proposed as an alternative design choice to address the latency arbitrage opportunities built in those markets. This paper studies the extent to which adaptive rules to define the length of the clearing intervals affect the performance of frequent call markets.

AAAI Conference 2019 Conference Paper

Heuristic Voting as Ordinal Dominance Strategies

• Omer Lev
• Reshef Meir
• Svetlana Obraztsova
• Maria Polukarov

Decision making under uncertainty is a key component of many AI settings, and in particular of voting scenarios where strategic agents are trying to reach a joint decision. The common approach to handle uncertainty is by maximizing expected utility, which requires a cardinal utility function as well as detailed probabilistic information. However, often such probabilities are not easy to estimate or apply. To this end, we present a framework that allows for “shades of gray” of likelihood without probabilities. Specifically, we create a hierarchy of sets of world states based on a prospective poll, with inner sets contain more likely outcomes. This hierarchy of likelihoods allows us to define what we term ordinally-dominated strategies. We use this approach to justify various known voting heuristics as bounded-rational strategies.

AAMAS Conference 2017 Conference Paper

Doodle Poll Games

• Svetlana Obraztsova
• Maria Polukarov
• Zinovi Rabinovich
• Edith Elkind

In Doodle polls, each voter approves a subset of the available alternatives according to his preferences. While such polls can be captured by the standard models of Approval voting, Zou et al. [18] analyse real-life Doodle poll data and conclude that poll participants’ behaviour seems to be affected by considerations other than their intrinsic preferences over the alternatives. To capture this phenomenon, they propose a model of social voting, where voters approve their top alternatives as well as additional ‘safe’ choices so as to appear cooperative. The predictions of this model turn out to be consistent with the real-life data. However, Zou et al. do not attempt to rationalise the voters’ behaviour in the context of social voting: they explicitly describe the voters’ strategies rather than explain how these strategies arise from voters’ preferences. In this paper, we complement the work of Zou et al. by putting forward a model in which the behaviour described by Zou et al. arises as an equilibrium strategy. In our model, a voter derives a bonus from approving each additional alternative, up to a certain cap. We show that trembling hand perfect Nash equilibria of our model behave consistently with the model of Zou et al. Importantly, placing a cap on the total bonus is an essential component of our model: in the absence of the cap, all Nash equilibria are very far from the behaviour observed in Doodle polls.

AIJ Journal 2017 Journal Article

Iterative voting and acyclic games

• Reshef Meir
• Maria Polukarov
• Jeffrey S. Rosenschein
• Nicholas R. Jennings

IJCAI Conference 2016 Conference Paper

Strategic Voting with Incomplete Information

• Ulle Endriss
• Svetlana Obraztsova
• Maria Polukarov
• Jeffrey S. Rosenschein

Classical results in social choice theory on the susceptibility of voting rules to strategic manipulation make the assumption that the manipulator has complete information regarding the preferences of the other voters. In reality, however, voters only have incomplete information, which limits their ability to manipulate. We explore how these limitations affect both the manipulability of voting rules and the dynamics of systems in which voters may repeatedly update their own vote in reaction to the moves made by others. We focus on the Plurality, Veto, k-approval, Borda, Copeland, and Maximin voting rules, and consider several types of information that are natural in the context of these rules, namely information on the current front-runner, on the scores obtained by each alternative, and on the majority graph induced by the individual preferences.

IJCAI Conference 2016 Conference Paper

Trembling Hand Equilibria of Plurality Voting

• Svetlana Obraztsova
• Zinovi Rabinovich
• Edith Elkind
• Maria Polukarov
• Nicholas R. Jennings

Trembling hand (TH) equilibria were introduced by Selten in 1975. Intuitively, these are Nash equilibria that remain stable when players assume that there is a small probability that other players will choose off-equilibrium strategies. This concept is useful for equilibrium refinement, i. e. , selecting the most plausible Nash equilibria when the set of all Nash equilibria can be very large, as is the case, for instance, for Plurality voting with strategic voters. In this paper, we analyze TH equilibria of Plurality voting. We provide an efficient algorithm for computing a TH best response and establish many useful properties of TH equilibria in Plurality voting games. On the negative side, we provide an example of a Plurality voting game with no TH equilibria, and show that it is NP-hard to check whether a given Plurality voting game admits a TH equilibrium where a specific candidate is among the election winners.

IJCAI Conference 2015 Conference Paper

Convergence to Equilibria in Strategic Candidacy

• Maria Polukarov
• Svetlana Obraztsova
• Zinovi Rabinovich
• Alexander Kruglyi
• Nicholas R. Jennings

We study equilibrium dynamics in candidacy games, in which candidates may strategically decide to enter the election or withdraw their candidacy, following their own preferences over possible outcomes. Focusing on games under Plurality, we extend the standard model to allow for situations where voters may refuse to return their votes to those candidates who had previously left the election, should they decide to run again. We show that if at the time when a candidate withdraws his candidacy, with some positive probability each voter takes this candidate out of his future consideration, the process converges with probability 1. This is in sharp contrast with the original model where the very existence of a Nash equilibrium is not guaranteed. We then consider the two extreme cases of this setting, where voters may block a withdrawn candidate with probabilities 0 or 1. In these scenarios, we study the complexity of reaching equilibria from a given initial point, converging to an equilibrium with a predermined winner or to an equilibrium with a given set of running candidates. Except for one easy case, we show that these problems are NP-complete, even when the initial point is fixed to a natural—truthful— state where all potential candidates stand for election.

AAAI Conference 2015 Conference Paper

On the Convergence of Iterative Voting: How Restrictive Should Restricted Dynamics Be?

• Svetlana Obraztsova
• Evangelos Markakis
• Maria Polukarov
• Zinovi Rabinovich
• Nicholas Jennings

We study convergence properties of iterative voting procedures. Such procedures are defined by a voting rule and a (restricted) iterative process, where at each step one agent can modify his vote towards a better outcome for himself. It is already known that if the iteration dynamics (the manner in which voters are allowed to modify their votes) are unrestricted, then the voting process may not converge. For most common voting rules this may be observed even under the best response dynamics limitation. It is therefore important to investigate whether and which natural restrictions on the dynamics of iterative voting procedures can guarantee convergence. To this end, we provide two general conditions on the dynamics based on iterative myopic improvements, each of which is sufficient for convergence. We then identify several classes of voting rules (including Positional Scoring Rules, Maximin, Copeland and Bucklin), along with their corresponding iterative processes, for which at least one of these conditions hold.

IJCAI Conference 2015 Conference Paper

Strategic Candidacy Games with Lazy Candidates

• Svetlana Obraztsova
• Edith Elkind
• Maria Polukarov
• Zinovi Rabinovich

In strategic candidacy games, both voters and candidates have preferences over the set of candidates, and candidates may strategically withdraw from the election in order to manipulate the outcome according to their preferences. In this work, we extend the standard model of strategic candidacy games by observing that candidates may find it costly to run an electoral campaign and may therefore prefer to withdraw if their presence has no effect on the election outcome. We study the Nash equilibria and outcomes of natural best-response dynamics in the resulting class of games, both from a normative and from a computational perspective, and compare them with the Nash equilibria of the standard model.

IJCAI Conference 2013 Conference Paper

Coalitional Games via Network Flows

• Talal Rahwan
• Tri-Dung Nguyen
• Tomasz P. Michalak
• Maria Polukarov
• Madalina Croitoru
• Nicholas R. Jennings

We introduce a new representation scheme for coalitional games, called coalition-flow networks (CF-NETs), where the formation of effective coalitions in a task-based setting is reduced to the problem of directing flow through a network. We show that our representation is intuitive, fully expressive, and captures certain patterns in a significantly more concise manner compared to the conventional approach. Furthermore, our representation has the flexibility to express various classes of games, such as characteristic function games, coalitional games with overlapping coalitions, and coalitional games with agent types. As such, to the best of our knowledge, CF-NETs is the first representation that allows for switching conveniently and efficiently between overlapping/nonoverlapping coalitions, with/without agent types. We demonstrate the efficiency of our scheme on the coalition structure generation problem, where near-optimal solutions for large instances can be found in a matter of seconds.

AAAI Conference 2012 Conference Paper

Optimizing Payments in Dominant-Strategy Mechanisms for Multi-Parameter Domains

• Lachlan Dufton
• Victor Naroditskiy
• Maria Polukarov
• Nicholas Jennings

In AI research, mechanism design is typically used to allocate tasks and resources to agents holding private information about their values for possible allocations. In this context, optimizing payments within the Groves class has recently received much attention, mostly under the assumption that agent’s private information is single-dimensional. Our work tackles this problem in multi-parameter domains. Specifically, we develop a generic technique to look for a best Groves mechanism for any given mechanism design problem. Our method is based on partitioning the spaces of agent values and payment functions into regions, on each of which we are able to define a feasible linear payment function. Under certain geometric conditions on partitions of the two spaces this function is optimal. We illustrate our method by applying it to the problem of allocating heterogeneous items.

IJCAI Conference 2011 Conference Paper

Considerate Equilibrium

• Martin Hoefer
• Michal Penn
• Maria Polukarov
• Alexander Skopalik
• Berthold V
• ouml; cking

We study the existence and computational complexity of coalitional stability concepts based on social networks. Our concepts represent a natural and rich combinatorial generalization of a recent notion termed partition equilibrium. We assume that players in a strategic game are embedded in a social (or, communication) network, and there are coordination constraints defining the set of coalitions that can jointly deviate in the game. A main feature of our approach is that players act in a "considerate" fashion to ignore potentially profitable (group) deviations if the change in their strategy may cause a decrease of utility to their neighbors in the network. We explore the properties of such considerate equilibria in application to the celebrated class of resource selection games (RSGs). Our main result proves existence of a super-strong considerate equilibrium in all symmetric RSGs with strictly increasing delays, for any social network among the players and feasible coalitions represented by the set of cliques. The existence proof is constructive and yields an efficient algorithm. In fact, the computed considerate equilibrium is a Nash equilibrium for a standard RSG, thus showing that there exists a state that is stable against selfish and considerate behavior simultaneously. Furthermore, we provide results on convergence of considerate dynamics.

AAMAS Conference 2010 Conference Paper

Coalition Formation with Spatial and Temporal Constraints

• Sarvapali D. Ramchurn
• Maria Polukarov
• Alessandro Farinelli
• Cuong Truong
• Nicholas R. Jennings

The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP). We show that this problem is NP-hard--in particular, it contains the well-known complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97\% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.

AAAI Conference 2010 Conference Paper

Convergence to Equilibria in Plurality Voting

• Reshef Meir
• Maria Polukarov
• Jeffrey Rosenschein
• Nicholas Jennings

Multi-agent decision problems, in which independent agents have to agree on a joint plan of action or allocation of resources, are central to AI. In such situations, agents’ individual preferences over available alternatives may vary, and they may try to reconcile these differences by voting. Based on the fact that agents may have incentives to vote strategically and misreport their real preferences, a number of recent papers have explored different possibilities for avoiding or eliminating such manipulations. In contrast to most prior work, this paper focuses on convergence of strategic behavior to a decision from which no voter will want to deviate. We consider scenarios where voters cannot coordinate their actions, but are allowed to change their vote after observing the current outcome. We focus on the Plurality voting rule, and study the conditions under which this iterative game is guaranteed to converge to a Nash equilibrium (i. e. , to a decision that is stable against further unilateral manipulations). We show for the first time how convergence depends on the exact attributes of the game, such as the tie-breaking scheme, and on assumptions regarding agents’ weights and strategies.

IJCAI Conference 2009 Conference Paper

• Zinovi Rabinovich
• Enrico Gerding
• Maria Polukarov
• Nicholas R. Jennings

Recently, efficient approximation algorithms for finding Nash equilibria have been developed for the interesting class of anonymous games, where a player’s utility does not depend on the identity of its opponents. In this paper, we tackle the problem of computing equilibria in such games with continuous player types, extending the framework to encompass settings with imperfect information. In particular, given the existence result for pure Bayes-Nash equilibiria in these games, we generalise the fictitious play algorithm by developing a novel procedure for finding a best response strategy, which is specifically designed to deal with continuous and, therefore, infinite type spaces. We then combine the best response computation with the general fictitious play structure to obtain an equilibrium. To illustrate the power of this approach, we apply our algorithm to the domain of simultaneous auctions with continuous private values and discrete bids, in which the algorithm shows quick convergence.

AAMAS Conference 2009 Conference Paper

The Price of Democracy in Coalition Formation

• Georgios Chalkiadakis
• Edith Elkind
• Maria Polukarov
• Nicholas R. Jennings

Whenever rational agents form coalitions to execute tasks, doing so via a decentralized negotiation process—while more robust and democratic—may lead to a loss of efficiency compared to a centralized solution. To quantify this loss, we introduce the notion of the Price of Democracy (PoD), which measures the amount of resources needlessly committed to the task(s) at hand. After defining this concept for general coalitional games, we instantiate it in the setting of weighted voting games, a simple but expressive class of coalitional games that can be used to model resource allocation in multiagent scenarios. We approach the problem of forming winning coalitions in this setting from a non-cooperative perspective, and put forward an intuitive deterministic bargaining process, which exhibits no delay of agreement (i. e. , the agents are guaranteed to form a winning coalition in round one) and allows for efficient computation of bargaining strategies. We show a tight bound of 3/2 on the PoD of our process if two rounds of bargaining are allowed, and demonstrate that this bound cannot improve with more rounds. We then generalize our bargaining process to settings where multiple coalitions are allowed to be formed, show that this generalization also exhibits no delay of agreement, and discuss the PoD in such settings.

AAMAS Conference 2008 Conference Paper

Asynchronous Congestion Games

• Michal Penn
• Maria Polukarov
• Moshe Tennenholtz

We introduce a new class of games, asynchronous congestion games (ACGs). In an ACG, each player has a task that can be carried out by any element of a set of resources, and each resource executes its assigned tasks in a random order. Each player’s aim is to minimize his expected cost which is the sum of two terms – the sum of the fixed costs over the set of his utilized resources and the expected cost of his task execution. The cost of a player’s task execution is determined by the earliest time his task is completed, and thus it might be beneficial for him to assign his task to several resources. We prove the existence of pure strategy Nash equilibria in ACGs. Moreover, we present a polynomial time algorithm for finding such an equilibrium in a given ACG.