A Complete Epistemic Logic for Multiple Agents

1997 ◽  
pp. 35-68 ◽  
Author(s):  
W. Van der Hoek ◽  
J. J. Meyer
Keyword(s):  
Epistemic Logic ◽  
Multiple Agents

scholarly journals Truthful fair division without free disposal

2020 ◽  
Vol 55 (3) ◽  
pp. 523-545 ◽  
Author(s):  
Xiaohui Bei ◽  
Guangda Huzhang ◽  
Warut Suksompong
Keyword(s):  
Fair Division ◽  
Multiple Agents ◽  
Two Agents ◽  
Free Disposal ◽  
Cake Cutting ◽  
Strategic Agents ◽  
Additional Constraints

Abstract We study the problem of fairly dividing a heterogeneous resource, commonly known as cake cutting and chore division, in the presence of strategic agents. While a number of results in this setting have been established in previous works, they rely crucially on the free disposal assumption, meaning that the mechanism is allowed to throw away part of the resource at no cost. In the present work, we remove this assumption and focus on mechanisms that always allocate the entire resource. We exhibit a truthful and envy-free mechanism for cake cutting and chore division for two agents with piecewise uniform valuations, and we complement our result by showing that such a mechanism does not exist when certain additional constraints are imposed on the mechanisms. Moreover, we provide bounds on the efficiency of mechanisms satisfying various properties, and give truthful mechanisms for multiple agents with restricted classes of valuations.

Introducing Justification into Epistemic Logic

2005 ◽  
Vol 15 (6) ◽  
pp. 1059-1073 ◽  
Author(s):  
Sergei Artemov ◽  
Elena Nogina
Keyword(s):  
Epistemic Logic

Spreading the blame: The allocation of responsibility amongst multiple agents

Cognition ◽  
2010 ◽  
Vol 115 (1) ◽  
pp. 166-171 ◽  
Author(s):  
Tobias Gerstenberg ◽  
David A. Lagnado
Keyword(s):  
Multiple Agents

Information Acquisition Policies for Resource Allocation Among Multiple Agents

1997 ◽  
Vol 8 (2) ◽  
pp. 151-170 ◽  
Author(s):  
J. C. Moore ◽  
H. R. Rao ◽  
A. Whinston ◽  
K. Nam ◽  
T. S. Raghu
Keyword(s):  
Resource Allocation ◽  
Information Acquisition ◽  
Multiple Agents

INTERPERSONAL COORDINATION AND EPISTEMIC SUPPORT FOR INTENTIONS WITH WE-CONTENT

2010 ◽  
Vol 26 (3) ◽  
pp. 345-367 ◽  
Author(s):  
Olivier Roy
Keyword(s):  
Game Theory ◽  
Epistemic Logic ◽  
The Other ◽  
Interpersonal Coordination ◽  
Epistemic Game Theory ◽  
Cast Doubt ◽  
Alternative Set

In this paper I study intentions of the form ‘I intend that we . . .’, that is, intentions with a we-content, and their role in interpersonal coordination. I focus on the notion of epistemic support for such intentions. Using tools from epistemic game theory and epistemic logic, I cast doubt on whether such support guarantees the other agents' conditional mediation in the achievement of such intentions, something that appears important if intentions with a we-content are to count as genuine intentions. I then formulate a stronger version of epistemic support, one that does indeed ensure the required mediation, but I then argue that it rests on excessively strong informational conditions. In view of this I provide an alternative set of conditions that are jointly sufficient for coordination in games, and I argue that these conditions constitute a plausible alternative to the proposed notion of epistemic support.

Multi-itinerary optimization as cloud service

2021 ◽  
Vol 64 (11) ◽  
pp. 121-129
Author(s):  
Alexandru Cristian ◽  
Luke Marshall ◽  
Mihai Negrea ◽  
Flavius Stoichescu ◽  
Peiwei Cao ◽  
...  
Keyword(s):  
Travel Time ◽  
Time Windows ◽  
Algorithm Design ◽  
Cloud Service ◽  
Multiple Agents ◽  
Solution Quality ◽  
Traffic Conditions ◽  
Time Distance ◽  
And Performance ◽  
Vehicle Capacity

In this paper, we describe multi-itinerary optimization (MIO)---a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their routes to minimize travel time or distance. MIO can be used by organizations with a fleet of vehicles and drivers, mobile salesforce, or a team of personnel in the field, to maximize workforce efficiency. It supports a variety of constraints, such as service time windows, duration, priority, pickup and delivery dependencies, and vehicle capacity. MIO also considers traffic conditions between locations, resulting in algorithmic challenges at multiple levels (e.g., calculating time-dependent travel-time distance matrices at scale and scheduling services for multiple agents). To support an end-to-end cloud service with turnaround times of a few seconds, our algorithm design targets a sweet spot between accuracy and performance. Toward that end, we build a scalable approach based on the ALNS metaheuristic. Our experiments show that accounting for traffic significantly improves solution quality: MIO finds efficient routes that avoid late arrivals, whereas traffic-agnostic approaches result in a 15% increase in the combined travel time and the lateness of an arrival. Furthermore, our approach generates itineraries with substantially higher quality than a cutting-edge heuristic (LKH), with faster running times for large instances.

A Monge Sequence-Based Approach to Characterize the Competitive Newsvendor Problem

2021 ◽  
Author(s):  
Saurabh Bansal ◽  
Mahesh Nagarajan
Keyword(s):  
Structural Properties ◽  
Transportation Problem ◽  
Cash Flows ◽  
Newsvendor Problem ◽  
Multiple Agents ◽  
Optimization Framework ◽  
Unmet Demand ◽  
Game Theoretic

Replicating cash flows of multiple agents in game-theoretic settings tends to be a challenging task. In this paper, we consider the competitive newsvendor game where multiple newsvendors choose inventory levels before demand arrival and the unmet demand of each newsvendor spills over to multiple other newsvendors. We show that this spillover behavior and the resulting cash flows of each newsvendor can be replicated within a transportation problem after assigning artificial costs on spillover behavior. This replication provides an opportunity to study structural properties of the problem, as well as determine the equilibrium of the game. This paradigm of using artificial costs within an optimization framework to replicate agents’ cash flows can be used in many other games as well.

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