skip to main content


Title: Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction
Successfully navigating the social world requires reasoning about both high-level strategic goals, such as whether to cooperate or compete, as well as the low-level actions needed to achieve those goals. While previous work in experimental game theory has examined the former and work on multi-agent systems has examined the later, there has been little work investigating behavior in environments that require simultaneous planning and inference across both levels. We develop a hierarchical model of social agency that infers the intentions of other agents, strategically decides whether to cooperate or compete with them, and then executes either a cooperative or competitive planning program. Learning occurs across both high-level strategic decisions and low-level actions leading to the emergence of social norms. We test predictions of this model in multi-agent behavioral experiments using rich video-game like environments. By grounding strategic behavior in a formal model of planning, we develop abstract notions of both cooperation and competition and shed light on the computational nature of joint intentionality.  more » « less
Award ID(s):
1643413
NSF-PAR ID:
10026426
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
COGSCI
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    In anagram games, players are provided with letters for forming as many words as possible over a specified time duration. Anagram games have been used in controlled experiments to study problems such as collective identity, effects of goal setting, internal-external attributions, test anxiety, and others. The majority of work on anagram games involves individual players. Recently, work has expanded to group anagram games where players cooperate by sharing letters. In this work, we analyze experimental data from online social networked experiments of group anagram games. We develop mechanistic and data driven models of human decision-making to predict detailed game player actions (e.g., what word to form next). With these results, we develop a composite agent-based modeling and simulation platform that incorporates the models from data analysis. We compare model predictions against experimental data, which enables us to provide explanations of human decision-making and behavior. Finally, we provide illustrative case studies using agent-based simulations to demonstrate the efficacy of models to provide insights that are beyond those from experiments alone. 
    more » « less
  2. null (Ed.)
    PURPOSE: Firms do not continue and prosper purely on their own individual endeavors, as each firm is influenced by the activities of others, and thus direct and indirect relationships shape the firm’s strategic management. These relationships form the tactics by which knowledge and other strategically important resources are accessed and created. Forming and maintaining ties among members of a network have been the subject of numerous research studies in the social, economic, and business literature. Our work is framed by the resource-based view of the firm perspective along with social capital theory and its shared constructs in network theory. Prior findings suggest that networking ties are strategic actions generated for firm growth and continuance. The ties may be short-term or develop into long-term relationships. The intent of this research is to fill some of the gaps in interorganizational networking strategy by analyzing five antecedents that have been suggested in the literature as individually associated with entrepreneurs’ engagement in network ties. In this way, our work provides another research avenue for examining networking’s contribution to strategic management. We hypothesized positive connections to entrepreneurs’ engagement in network ties from antecedents involving the firm’s knowledge absorptive capacity, business goals, entrepreneurial orientation, social interactions, and support from their environment. METHODOLOGY: In our quantitative approach, we tested our proposed macrolevel direct and moderating connections through an online survey of 125 U.S. apparel manufacturing firms. The apparel manufacturing sector in the U.S., as in many countries, has struggled with multiple disrupting factors contributing to the sector’s decline in firm continuance. FINDINGS: The results from OLS regression analyses support our hypothesized connections in that each of the five antecedents significantly contributed to entrepreneurs’ engagement in network ties; however, when all five were collectively examined only absorptive capacity, social interaction, and business goals were significant (R2 = 0.58). Further examination of moderation effects found the entrepreneurs’ perceptions of a supportive environment to modify both entrepreneurial orientation and business goals. RESEARCH AND PRACTICAL IMPLICATIONS: The effects of a supportive environment on business goals’ relationship with network ties were greater when perceptions of a supportive environment decreased, while the effects of a supportive environment on entrepreneurship orientation’s relationship with network ties were greater when perceptions of a supportive environment increased suggesting further study of U.S. entrepreneurs’ perceptions of their environments. Entrepreneurs’ interested in building domestic and international supply chain ties may find network ties provide one solution for adapting the firm’s resources for global competitiveness. Future studies may direct attention to other industry sectors or countries for replication with larger sample sizes as we recognize the limitations to generalizability and scale refinement due to our limited sample size. ORIGINALITY AND VALUE: The examination of five constructs to shed light on how an organization’s decisions may relate to engaging in networks and provides theoretical as well as practical implications that contribute to the larger organizational system framework. 
    more » « less
  3. Abstract

    Collaboration requires agents to coordinate their behavior on the fly, sometimes cooperating to solve a single task together and other times dividing it up into sub‐tasks to work on in parallel. Underlying the human ability to collaborate is theory‐of‐mind (ToM), the ability to infer the hidden mental states that drive others to act. Here, we develop Bayesian Delegation, a decentralized multi‐agent learning mechanism with these abilities. Bayesian Delegation enables agents to rapidly infer the hidden intentions of others by inverse planning. We test Bayesian Delegation in a suite of multi‐agent Markov decision processes inspired by cooking problems. On these tasks, agents with Bayesian Delegation coordinate both their high‐level plans (e.g., what sub‐task they should work on) and their low‐level actions (e.g., avoiding getting in each other's way). When matched with partners that act using the same algorithm, Bayesian Delegation outperforms alternatives. Bayesian Delegation is also a capable ad hoc collaborator and successfully coordinates with other agent types even in the absence of prior experience. Finally, in a behavioral experiment, we show that Bayesian Delegation makes inferences similar to human observers about the intent of others. Together, these results argue for the centrality of ToM for successful decentralized multi‐agent collaboration.

     
    more » « less
  4. Firms do not continue and prosper purely on their own individual endeavors, as each firm is influenced by the activities of others, and thus direct and indirect relationships shape the firm’s strategic management. These relationships form the tactics by which knowledge and other strategically important resources are accessed and created. Forming and maintaining ties among members of a network have been the subject for numerous research studies in the social, economic, and business literature. Our work is framed by the resource-based view of the firm perspective along with social capital theory and its shared constructs in network theory. Prior findings suggest that networking ties are strategic actions generated for firm growth and continuance. The ties may be short-term or develop into long-term relationships. The purpose of this research is to fill some of the gaps in interorganizational networking strategy by analyzing five antecedents that have been suggested in the literature as individually associated with entrepreneurs’ engagement in network ties. In this way, our work provides another research avenue for examining networking’s contribution to strategic management. We hypothesized positive connections to entrepreneurs’ engagement in network ties from antecedents involving the firm’s knowledge absorptive capacity, business goals, entrepreneurial orientation, social interactions, and support from their environment. We tested our proposed macrolevel direct and moderating connections through an online survey of 125 U.S. apparel manufacturing firms. The apparel manufacturing sector in the U.S., as in many countries, has struggled with multiple disrupting factors contributing to the sector’s decline in firm continuance. Networks, serving to build domestic and international supply chain ties, may provide one solution for adapting the firm’s resources enhancing global competitiveness. Findings from OLS regression analyses support our hypothesized connections in that each of the five antecedents significantly contributed to entrepreneurs’ engagement in network ties; however, when all five were collectively examined only absorptive capacity, social interaction, and business goals were significant (R2 = 0.58). Further examination of moderation effects found the entrepreneurs’ perceptions of a supportive environment to modify both entrepreneurial orientation and business goals. The effects of a supportive environment on business goals’ relationship with network ties were greater when perceptions of a supportive environment decreased, while the effects of a supportive environment on entrepreneurship orientation’s relationship with network ties were greater when perceptions of a supportive environment increased. Future studies may direct attention to other industry sectors or countries for replication with larger sample sizes as we recognize the limitations to generalizability and scale refinement due to our limited sample size. Examining the five constructs sheds light on how an organization’s decisions may relate to engaging in networking and provides theoretical as well as practical implications that contributes to the larger organizational system framework. This dataset contains responses from 97 U.S. apparel manufacturers collected via an online survey during the fall of 2019. The apparel manufacturing sector in the U.S., as in many countries, has struggled with multiple disrupting factors contributing to the sector’s decline in firm continuance. Networks, serving to build domestic and international supply chain ties, may provide one solution for adapting the firm’s resources enhancing global competitiveness. The purpose of the study was to examine connections to entrepreneurs’ engagement in network ties from antecedents involving the firm’s knowledge absorptive capacity, business goals, entrepreneurial orientation, social interactions, and support from their environment. 
    more » « less
  5. null (Ed.)
    Cooperatively avoiding collision is a critical functionality for robots navigating in dense human crowds, failure of which could lead to either overaggressive or overcautious behavior. A necessary condition for cooperative collision avoidance is to couple the prediction of the agents’ trajectories with the planning of the robot’s trajectory. However, it is unclear that trajectory based cooperative collision avoidance captures the correct agent attributes. In this work we migrate from trajectory based coupling to a formalism that couples agent preference distributions. In particular, we show that preference distributions (probability density functions representing agents’ intentions) can capture higher order statistics of agent behaviors, such as willingness to cooperate. Thus, coupling in distribution space exploits more information about inter-agent cooperation than coupling in trajectory space. We thus introduce a general objective for coupled prediction and planning in distribution space, and propose an iterative best response optimization method based on variational analysis with guaranteed sufficient decrease. Based on this analysis, we develop a sampling-based motion planning framework called DistNav1 that runs in real time on a laptop CPU. We evaluate our approach on challenging scenarios from both real world datasets and simulation environments, and benchmark against a wide variety of model based and machine learning based approaches. The safety and efficiency statistics of our approach outperform all other models. Finally, we find that DistNav is competitive with human safety and efficiency performance. 
    more » « less