scholarly journals Individual exploration and selective social learning: Balancing exploration-exploitation trade-offs in collective foraging

2021 ◽  
Author(s):  
Ketika Garg ◽  
Christopher T. Kello ◽  
Paul E Smaldino
Keyword(s):  
Social Learning ◽  
Social Information ◽  
Social Cues ◽  
Optimal Combination ◽  
Trade Off ◽  
Trade Offs ◽  
Lévy Walks ◽  
Power Law Exponent ◽  
Collective Foraging ◽  
Exploration Exploitation

Search requires balancing exploring for more options and exploiting the ones previously found. Individuals foraging in a group face another trade-off: whether to engage in social learning to exploit the solutions found by others or to solitarily search for unexplored solutions. Social learning can decrease the costs of finding new resources, but excessive social learning can decrease the exploration for new solutions. We study how these two trade-offs interact to influence search efficiency in a model of collective foraging under conditions of varying resource abundance, resource density, and group size. We modeled individual search strategies as Lévy walks, where a power-law exponent (μ) controlled the trade-off between exploitative and explorative movements in individual search. We modulated the trade-off between individual search and social learning using a selectivity parameter that determined how agents responded to social cues in terms of distance and likely opportunity costs. Our results show that social learning is favored in rich and clustered environments, but also that the benefits of exploiting social information are maximized by engaging in high levels of individual exploration. We show that selective use of social information can modulate the disadvantages of excessive social learning, especially in larger groups and with limited individual exploration. Finally, we found that the optimal combination of individual exploration and social learning gave rise to trajectories with μ ≈ 2 and provide support for the general optimality such patterns in search. Our work sheds light on the interplay between individual search and social learning, and has broader implications for collective search and problem-solving.

scholarly journals Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-start Users

2021 ◽  
Vol 39 (4) ◽  
pp. 1-29
Author(s):  
Shijun Li ◽  
Wenqiang Lei ◽  
Qingyun Wu ◽  
Xiangnan He ◽  
Peng Jiang ◽  
...  
Keyword(s):  
State Of The Art ◽  
Cold Start ◽  
User Preference ◽  
Inherent Limitation ◽  
Trade Off ◽  
Thompson Sampling ◽  
Trade Offs ◽  
Benchmark Datasets ◽  
Item Attributes ◽  
Exploration Exploitation

Static recommendation methods like collaborative filtering suffer from the inherent limitation of performing real-time personalization for cold-start users. Online recommendation, e.g., multi-armed bandit approach, addresses this limitation by interactively exploring user preference online and pursuing the exploration-exploitation (EE) trade-off. However, existing bandit-based methods model recommendation actions homogeneously. Specifically, they only consider the items as the arms, being incapable of handling the item attributes , which naturally provide interpretable information of user’s current demands and can effectively filter out undesired items. In this work, we consider the conversational recommendation for cold-start users, where a system can both ask the attributes from and recommend items to a user interactively. This important scenario was studied in a recent work  [54]. However, it employs a hand-crafted function to decide when to ask attributes or make recommendations. Such separate modeling of attributes and items makes the effectiveness of the system highly rely on the choice of the hand-crafted function, thus introducing fragility to the system. To address this limitation, we seamlessly unify attributes and items in the same arm space and achieve their EE trade-offs automatically using the framework of Thompson Sampling. Our Conversational Thompson Sampling (ConTS) model holistically solves all questions in conversational recommendation by choosing the arm with the maximal reward to play. Extensive experiments on three benchmark datasets show that ConTS outperforms the state-of-the-art methods Conversational UCB (ConUCB) [54] and Estimation—Action—Reflection model [27] in both metrics of success rate and average number of conversation turns.

scholarly journals Social transmission of egg rejection in a cuckoo host

2020 ◽  
Author(s):  
Canchao Yang ◽  
William E Feeney
Keyword(s):  
Social Learning ◽  
Brood Parasitism ◽  
Social Information ◽  
Social Cues ◽  
Egg Rejection ◽  
Dynamic Nature ◽  
Brood Parasites ◽  
The Social ◽  
Rapid Dissemination ◽  
Barn Swallows

AbstractSocial learning can enable the rapid dissemination of behaviors throughout a population. Rejection of foreign eggs is a key defense in hosts of avian brood parasites; however, whether social cues can inform whether a host rejects an egg remains unknown. Here, we aimed to determine whether access to social information can influence egg rejection behavior in semi-colonial barn swallows (Hirundo rustica). By manipulating the social information available from a neighboring nest, we found that swallows that had access to social information (i.e. neighbor recently rejected an egg) were more likely to reject a foreign egg compared to those that did not have access to social information (i.e. neighbor did not reject an egg). This result provides the first empirical evidence that egg rejection behavior can solely be informed by social information, and in doing so highlights the dynamic nature of defenses that hosts can deploy against brood parasitism.

scholarly journals Copy-when-uncertain: bumblebees rely on social information when rewards are highly variable

2016 ◽  
Vol 12 (6) ◽  
pp. 20160188 ◽  
Author(s):  
Marco Smolla ◽  
Sylvain Alem ◽  
Lars Chittka ◽  
Susanne Shultz
Keyword(s):  
Social Learning ◽  
Personal Information ◽  
Social Information ◽  
Information Use ◽  
Social Cues ◽  
Agent Based Model ◽  
Agent Based ◽  
Variable Environments ◽  
Foraging Decisions

To understand the relative benefits of social and personal information use in foraging decisions, we developed an agent-based model of social learning that predicts social information should be more adaptive where resources are highly variable and personal information where resources vary little. We tested our predictions with bumblebees and found that foragers relied more on social information when resources were variable than when they were not. We then investigated whether socially salient cues are used preferentially over non-social ones in variable environments. Although bees clearly used social cues in highly variable environments, under the same conditions they did not use non-social cues. These results suggest that bumblebees use a ‘copy-when-uncertain’ strategy.

scholarly journals Individual differences in learning behaviours in humans: Asocial exploration tendency does not predict reliance on social learning

2016 ◽  
Author(s):  
Wataru Toyokawa ◽  
Yoshimatsu Saito ◽  
Tatsuya Kameda
Keyword(s):  
Individual Differences ◽  
Social Learning ◽  
Learning Strategies ◽  
Learning Strategy ◽  
Empirical Studies ◽  
Social Information ◽  
Information Use ◽  
The Social ◽  
Social Information Use ◽  
Exploration Exploitation

AbstractA number of empirical studies have suggested that individual differences in asocial exploration tendencies in animals may be related to those in social information use. However, because the ‘exploration tendency’ in most previous studies has been measured without considering the exploration-exploitation trade-off, it is yet hard to conclude that the animal asocial ‘exploration-exploitation’ tendency may be tied to social information use. Here, we studied human learning behaviour in both asocial and social multi-armed bandit tasks. By fitting reinforcement learning models including asocial and/or social decision processes, we measured each individual’s (1) asocial exploration tendency and (2) social information use. We found consistent individual differences in the exploration tendency in the asocial tasks. We also found substantive heterogeneity in the adopted learning strategies in the social task: One-third of participants were most likely to have used the copy-when-uncertain strategy, while the remaining two-thirds were most likely to have relied only on asocial learning. However, we found no significant individual association between the exploration frequency in the asocial task and the use of the social learning strategy in the social task. Our results suggest that the social learning strategies may be independent from the asocial search strategies in humans.

scholarly journals Specialization and selective social attention establishes the balance between individual and social learning

2021 ◽  
Author(s):  
Charley M. Wu ◽  
Mark K. Ho ◽  
Benjamin Kahl ◽  
Christina Leuker ◽  
Björn Meder ◽  
...  
Keyword(s):  
Social Learning ◽  
Social Interactions ◽  
Field Data ◽  
Field Of View ◽  
Game Engine ◽  
Foraging Patterns ◽  
Trade Off ◽  
Collective Foraging ◽  
Simulation Results ◽  
Spatial Trajectories

AbstractA key question individuals face in any social learning environment is when to innovate alone and when to imitate others. Previous simulation results have found that the best performing groups exhibit an intermediate balance, yet it is still largely unknown how individuals collectively negotiate this balance. We use an immersive collective foraging experiment, implemented in the Minecraft game engine, facilitating unprecedented access to spatial trajectories and visual field data. The virtual environment imposes a limited field of view, creating a natural trade-off between allocating visual attention towards individual innovation or to look towards peers for social imitation. By analyzing foraging patterns, social interactions (visual and spatial), and social influence, we shine new light on how groups collectively adapt to the fluctuating demands of the environment through specialization and selective imitation, rather than homogeneity and indiscriminate copying of others.

scholarly journals The exploration-exploitation trade-off in a foraging task is affected by mood-related arousal and valence

2021 ◽  
Author(s):  
Roel van Dooren ◽  
Roy de Kleijn ◽  
Bernhard Hommel ◽  
Zsuzsika Sjoerds
Keyword(s):  
Foraging Behavior ◽  
Mood Induction ◽  
Negative Mood ◽  
Interindividual Differences ◽  
Trade Off ◽  
Marginal Value ◽  
Trade Offs ◽  
Foraging Task ◽  
Exploration Exploitation ◽  
Arousal And Valence

AbstractThe exploration-exploitation trade-off shows conceptual, functional, and neural analogies with the persistence-flexibility trade-off. We investigated whether mood, which is known to modulate the persistence-flexibility balance, would similarly affect the exploration-exploitation trade-off in a foraging task. More specifically, we tested whether interindividual differences in foraging behavior can be predicted by mood-related arousal and valence. In 119 participants, we assessed mood-related interindividual differences in exploration-exploitation using a foraging task that included minimal task constraints to reduce paradigm-induced biases of individual control tendencies. We adopted the marginal value theorem as a model-based analysis approach, which approximates optimal foraging behavior by tackling the patch-leaving problem. To assess influences of mood on foraging, participants underwent either a positive or negative mood induction. Throughout the experiment, we assessed arousal and valence levels as predictors for explorative/exploitative behavior. Our mood manipulation affected participants' arousal and valence ratings as expected. Moreover, mood-related arousal was found to predict exploration while valence predicted exploitation, which only partly matched our expectations and thereby the proposed conceptual overlap with flexibility and persistence, respectively. The current study provides a first insight into how processes related to arousal and valence differentially modulate foraging behavior. Our results imply that the relationship between exploration-exploitation and flexibility-persistence is more complicated than the semantic overlap between these terms might suggest, thereby calling for further research on the functional, neural, and neurochemical underpinnings of both trade-offs.

scholarly journals Social information can undermine individual performance in exploration-exploitation tasks

2018 ◽  
Author(s):  
Kyanoush Seyed Yahosseini ◽  
Samuli Reijula ◽  
Lucas Molleman ◽  
Mehdi Moussaid
Keyword(s):  
Daily Life ◽  
Social Information ◽  
Individual Performance ◽  
Individual Factors ◽  
Experimental Paradigm ◽  
Individual Decision ◽  
Decision Strategies ◽  
Individual Decision Making ◽  
Trade Off ◽  
Exploration Exploitation

In many daily life situations, people face decisions involving a trade-off between exploring new options and exploiting known ones. In these situations, observing the decisions of others can influence people’s decisions. Whereas social information often helps making better decisions, research has suggested that under certain conditions it can be detrimental. How precisely social information influences decision strategies and impacts performance is, however, disputed. Here we study how social information influences individuals’ exploration-exploitation trade-off and show that this adaptation can undermine their performance. Using a minimal experimental paradigm, we find that participants tend to copy the solution of other individuals too rapidly, thus decreasing the likelihood of discovering a better solution. Approximating this behavior with a simple model suggests, that individuals’ willingness to explore only depends on the value of known existing solutions. Our results allow for a better understanding of the interplay between social and individual factors in individual decision-making.

An Exploration/Exploitation Trade-off Between Mind-Wandering and Goal-Directed Thinking

2018 ◽  
Author(s):  
Chandra S. Sripada
Keyword(s):  
Computer Science ◽  
Mind Wandering ◽  
Trade Off ◽  
Cognitive Domains ◽  
Trade Offs ◽  
Directed Thinking ◽  
New Perspective ◽  
Exploration Exploitation ◽  
Directed Thought

Agents invariably face trade-offs between exploration, which increases informational stores and potentially opens up new opportunities, and exploitation, which utilizes existing informational stores to take advantage of known opportunities. This exploration/exploitation trade-off has been extensively studied in computer science and has been productively applied to multiple cognitive domains. In this chapter, this framework is extended to the ubiquitous alternation between two modes of serial thought: mind-wandering and goal-directed thought. The exploration/exploitation framework provides a new perspective on the functionality of mind-wandering and its pattern of regular switching with goal-directed thought. It also raises new hypotheses about the regulation of mind-wandering across time and differences in the propensity to mind-wander across individuals.

Dual Goals for Speed and Accuracy on the Same Performance Task

2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt
Keyword(s):  
Memory Scanning ◽  
Performance Task ◽  
Performance Tasks ◽  
Trade Off ◽  
Test Experiment ◽  
Trade Offs ◽  
New Finding ◽  
Sternberg Paradigm ◽  
Speed Accuracy ◽  
Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

The Effects of Decision Time on Perceptions of Decisions and Decision Makers in (Moral) Trade-Off Scenarios

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Decision Time ◽  
Decision Makers ◽  
Process Information ◽  
Total N ◽  
Trade Off ◽  
Financial Gain ◽  
Trade Offs ◽  
Sacred Values ◽  
Moral Context

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.

Sign in / Sign up

Export Citation Format

Share Document