skip to main content

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Thursday, February 13 until 2:00 AM ET on Friday, February 14 due to maintenance. We apologize for the inconvenience.


Title: Distortion in Social Choice Problems: An Annotated Reading List.
The notion of distortion in social choice problems has been defined to measure the loss in efficiency - typically measured by the utilitarian social welfare, the sum of utilities of the participating agents - due to having access only to limited information about the preferences of the agents. Here, we provide a comprehensive reading list on the related literature.  more » « less
Award ID(s):
2006286 1527497
PAR ID:
10276080
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
SIGecom exchanges
Volume:
19
Issue:
1
ISSN:
1551-9031
Page Range / eLocation ID:
12-14
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. A multiagent system is a society of autonomous agents whose interactions can be regulated via social norms. In general, the norms of a society are not hardcoded but emerge from the agents’ interactions. Specifically, how the agents in a society react to each other’s behavior and respond to the reactions of others determines which norms emerge in the society. We think of these reactions by an agent to the satisfactory or unsatisfactory behaviors of another agent as communications from the first agent to the second agent. Understanding these communications is a kind of social intelligence: these communications provide natural drivers for norm emergence by pushing agents toward certain behaviors, which can become established as norms. Whereas it is well-known that sanctioning can lead to the emergence of norms, we posit that a broader kind of social intelligence can prove more effective in promoting cooperation in a multiagent system. Accordingly, we develop Nest, a framework that models social intelligence via a wider variety of communications and understanding of them than in previous work. To evaluate Nest, we develop a simulated pandemic environment and conduct simulation experiments to compare Nest with baselines considering a combination of three kinds of social communication: sanction, tell, and hint. We find that societies formed of Nest agents achieve norms faster. Moreover, Nest agents effectively avoid undesirable consequences, which are negative sanctions and deviation from goals, and yield higher satisfaction for themselves than baseline agents despite requiring only an equivalent amount of information. 
    more » « less
  2. null (Ed.)
    This work investigates how social agents can be designed to create a sense of ownership over them within a group of users. Social agents, such as conversational agents and chatbots, currently interact with people in impersonal, isolated, and often one-on-one interactions: one user and one agent. This is likely to change as agents become more socially sophisticated and integrated in social fabrics. Previous research has indicated that understanding who owns an agent can assist in creating expectations and understanding who an agent is accountable to within a group. We present findings from a three week case-study in which we implemented a chatbot that was successful in creating a sense of collective ownership within a community. We discuss the design choices that led to this outcome and implications for social agent design. 
    more » « less
  3. Altafini, Claudio ; Como, Giacomo ; Hendrickx, Julien M. ; Olshevsky, Alexander ; Tahbez-Salehi, Alireza (Ed.)
    We study a social learning model in which agents iteratively update their beliefs about the true state of the world using private signals and the beliefs of other agents in a non-Bayesian manner. Some agents are stubborn, meaning they attempt to convince others of an erroneous true state (modeling fake news). We show that while agents learn the true state on short timescales, they "forget" it and believe the erroneous state to be true on longer timescales. Using these results, we devise strategies for seeding stubborn agents so as to disrupt learning, which outperform intuitive heuristics and give novel insights regarding vulnerabilities in social learning. 
    more » « less
  4. null (Ed.)
    Agents that support spoken interaction (e.g., Amazon Echo) are designed for social spaces like the home, yet designers know little about how they should respond to social activity around them. We set out to reconsider current one-on-one interactions with agents, and explore the design space of future socially sophisticated agents. To do so, we use an iterative co-design process with designers and theatre experts to devise an immersive performance, "Robotic Futures." Theatre is a form of knowing through doing-by examining the interactions that persisted in the devising process and those that fell through, we conclude with a proposition for design considerations for future agents. Based on emerging research in this space, we focus on the characteristics of personally-owned agents in comparison to shared agents, and consider the roles and functions each introduce in their integration in the home. 
    more » « less
  5. null (Ed.)
    Virtual agents are systems that add a social dimension to computing, often featuring not only natural language input but also an embodiment or avatar. This allows them to take on a more social role and leverage the use of nonverbal communication (NVC). In humans, NVC is used for many purposes, including communicating intent, directing attention, and conveying emotion. As a result, researchers have developed agents that emulate these behaviors. However, challenges pervade the design and development of NVC in agents. Some articles reveal inconsistencies in the benefits of agent NVC; others show signs of difficulties in the process of analyzing and implementing behaviors. Thus, it is unclear what the specific outcomes and effects of incorporating NVC in agents and what outstanding challenges underlie development. This survey seeks to review the uses, outcomes, and development of NVC in virtual agents to identify challenges and themes to improve and motivate the design of future virtual agents. 
    more » « less