Author name cluster

Julian Chingoma

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers

2 author rows

ECAI Conference 2025 Conference Paper

Apportionment with Weighted Seats

Julian Chingoma
Ulle Endriss
Ronald de Haan
Adrian Haret
Jan Maly 0001

Apportionment is the task of assigning resources to entities with different entitlements in a fair manner, and specifically a manner that is as proportional as possible. The best-known application is the assignment of parliamentary seats to political parties based on their share in the popular vote. Here we enrich the standard model of apportionment by associating each seat with a weight representing the (objective) value of that seat. A seat’s weight reflects the fact that different seats might come with different roles, such as chair or treasurer. We define several apportionment methods and natural fairness requirements for this new setting, and we study the extent to which our methods satisfy these requirements. Our findings show that full fairness is harder to achieve than in the standard apportionment setting. Yet, for several natural relaxations of those requirements we can achieve stronger results than in the more expressive model of fair division with entitlements, where the values of objects are subjective.

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IJCAI Conference 2023 Conference Paper

Deliberation as Evidence Disclosure: A Tale of Two Protocol Types

Julian Chingoma
Adrian Haret

We study a model inspired by deliberative practice, in which agents selectively disclose evidence about a set of alternatives prior to taking a final decision on them. We are interested in whether such a process, when iterated to termination, results in the objectively best alternatives being selected—thereby lending support to the idea that groups can be wise even when their members communicate with each other. We find that, under certain restrictions on the relative amounts of evidence, together with the actions available to the agents, there exist deliberation protocols in each of the two families we look at (i. e. , simultaneous and sequential) that offer desirable guarantees. Simulation results further complement this picture, by showing how the distribution of evidence among the agents influences parameters of interest, such as the outcome of the protocols and the number of rounds until termination.

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AAMAS Conference 2023 Conference Paper

Deliberation as Evidence Disclosure: A Tale of Two Protocol Types

Julian Chingoma
Adrian Haret

We propose a model inspired by deliberative practice in which agents selectively disclose evidence about alternatives prior to taking a final decision on them. We are interested in whether such a process results in the objectively best alternative getting elected, thereby lending support to the idea that groups can be wise even when their members communicate with each other. We find that, under certain restrictions on the relative amounts of evidence, together with the actions available to the agents, there exist deliberation protocols in each of the two families we look at (i. e. , simultaneous and sequential) that offer desirable guarantees. Simulation results further complement this picture, by showing how the distribution of evidence among the agents influences the outcome of the protocols.

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IJCAI Conference 2023 Conference Paper

Fairness and Stability in Complex Domains

Julian Chingoma

Fairness and stability are normative concepts that have been investigated for many social choice domains. Recently, increasing attention has fallen on richer, and more complex, settings and we look to develop, and study in depth, these fairness and stability notions in a variety of such complex domains.

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AAMAS Conference 2022 Conference Paper

Simulating Multiwinner Voting Rules in Judgment Aggregation

Julian Chingoma
Ulle Endriss
Ronald de Haan

We simulate voting rules for multiwinner elections in a model of judgment aggregation that distinguishes between rationality and feasibility constraints. These constraints restrict the structure of the individual judgments and of the collective outcome computed by the rule, respectively. We extend known results regarding the simulation of single-winner voting rules to the multiwinner setting, both for elections with ordinal preferences and for elections with approval-based preferences. This not only provides us with a new tool to analyse multiwinner elections, but it also suggests the definition of new judgment aggregation rules, by generalising some of the principles at the core of well-known multiwinner voting rules to this richer setting. We explore this opportunity with regards to the principle of proportionality. Finally, in view of the computational difficulty associated with many judgment aggregation rules, we investigate the computational complexity of our embeddings and of the new judgment aggregation rules we put forward.

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