Probability matching on a simple simulated foraging task:The effects of reward persistence and accumulation on choice behavior

Over a series of decisions between two or more probabilistically rewarded options, humans have a tendency to diversify their choices, even when this will lead to diminished overall reward. In the extreme case of probability matching, this tendency is expressed through allocation of choices in proportion to their likelihood of reward. Research suggests that this behaviour is an instinctive response, driven by heuristics, and that it may be overruled through the application of sufficient deliberation and self-control. However, if this is the case, then how and why did this response become established? The present study explores the hypothesis that diversification of choices, and potentially probability matching, represents an overextension of a historically normative foraging strategy. This is done through examining choice behaviour on a simple simulated foraging task, designed to model the natural process of accumulation of unharvested resources over time. Behaviour was then directly compared with that observed on a standard fixed probability task (cf. Ellerby & Tunney, 2017). Results indicated a convergence of choice patterns on the simulated foraging task, between participants who acted intuitively and those who took a more strategic approach. These findings are also compared with those of another similarly motivated study (Schulze, van Ravenzwaaij, & Newell, 2017)

A combined behavioural and electrophysiological examination of the faulty foraging theory of probability matching

Given a repeated choice between two or more options with fixed, independent and identically distributed reward probabilities, overall pay-offs can be maximized by the exclusive selection of the option with the greatest likelihood of reward. The tendency to match response proportions to reward contingencies is suboptimal. Nevertheless, this behaviour is well documented. This thesis had two core objectives. First, it was aimed to ascertain the relative contributions of several existing accounts of probability matching in determining choice behaviour, particularly regarding the maximization versus diversification of choices. These accounts include failed pattern matching, driven by apophenia, and a heuristic-driven response that can be overruled with sufficient deliberation. Second, to then further address potential mechanisms underlying whichever factor was found to make the most substantive contribution to choice behaviour, through the combined application of behavioural and electrophysiological methods. Over a series of behavioural studies, the use of strategy over intuition proved to be the most consistent and substantial predictor of maximizing choices, in robust support of the heuristic account. Given this finding, the question emerges of why probability matching is the dominant intuitive response. One possibility is that matching represents the overextension of an evolutionarily stable foraging strategy, an account termed the ‘Faulty Foraging Theory’. A simple simulated foraging task was designed to assess choice behaviour when reward schedules incorporate the factor of natural resource accumulation and depletion. The contrast in choice behaviour on this task with the standard probability matching preparation was consistent with the Faulty Foraging model. A series of electrophysiological studies were then conducted, in an attempt to uncover the putative illusory internal representation of reward accumulation on the standard task, which could drive suboptimal diversification of choices. This was ultimately unsuccessful. However, further corroborating electrophysiological evidence was obtained for the heuristic account, in the form of characteristic patterns of prefrontal activity relating to maximizing vs. diversification of choices

Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression

Most of statistics and AI draw insights through modelling discord or variance between sources (i.e., inter-source) of information. Increasingly however, research is focusing on uncertainty arising at the level of individual measurements (i.e., within- or intra-source), such as for a given sensor output or human response. Here, adopting intervals rather than numbers as the fundamental data-type provides an efficient, powerful, yet challenging way forward—offering systematic capture of uncertainty-at-source, increasing informational capacity, and ultimately potential for additional insight. Following progress in the capture of interval-valued data in particular from human participants, conducting machine learning directly upon intervals is a crucial next step. This paper focuses on linear regression for interval-valued data as a recent growth area, providing an essential foundation for broader use of intervals in AI. We conduct an in-depth analysis of state-of-the-art methods, elucidating their behaviour, advantages, and pitfalls when applied to synthetic and real-world data sets with different properties. Specific emphasis is given to the challenge of preserving mathematical coherence, i.e., models maintain fundamental mathematical properties of intervals. In support of real-world applicability of the regression methods, we introduce and demonstrate a novel visualization approach, the interval regression graph, or IRG , which effectively communicates the impact of both position and range of variables within the regression models—offering a leap in their interpretability. Finally, the paper provides practical recommendations concerning regression-method choice for interval data and highlights remaining challenges and important next steps for developing AI with the capacity to handle uncertainty-at-source

On the Relationship between Similarity Measures and Thresholds of Statistical Significance in the Context of Comparing Fuzzy Sets

Comparing fuzzy sets by computing their similarity is common, with a large set of measures of similarity available. However, while commonplace in the computational intelligence community, the application and results of similarity measures are less common in the wider scientific context, where statistical approaches are the standard for comparing distributions. This is challenging, as it means that developments around similarity measures arising from the fuzzy community are inaccessible to the wider scientific community; and that the fuzzy community fails to take advantage of a strong statistical understanding which may be applicable to comparing (fuzzy membership) functions. In this paper, we commence a body of work on systematically relating the outputs of similarity measures to the notion of statistically significant difference; that is, how (dis)similar do two fuzzy sets need to be for them to be statistically different? We explain that in this context it is useful to initially focus on dis-similarity, rather than similarity, as the former aligns directly with the widely used concept of statistical difference. We propose two methods of applying statistical tests to the outputs of fuzzy dissimilarity measures to determine significant difference. We show how the proposed work provides deeper insight into the behaviour and possible interpretation of degrees of dis-similarity and, consequently, similarity, and how the interpretation differs in respect to context (e.g., the complexity of the fuzzy sets)

The effects of heuristics and apophenia on probabilistic choice

Given a repeated choice between two or more options with independent and identically distributed reward probabilities, overall pay-offs can be maximized by the exclusive selection of the option with the greatest likelihood of reward. The tendency to match response proportions to reward contingencies is suboptimal. nevertheless, this behaviour is well documented. A number of explanatory accounts have been proposed for probability matching. These include failed pattern matching, driven by apophenia, and a heuristic-driven response that can be overruled with sufficient deliberation. We report two experiments that were designed to test the relative effects on choice behaviour of both an intuitive versus strategic approach to the task and belief that there was a predictable pattern in the reward sequence, through a combination of both direct experimental manipulation and post-experimental self-report. Mediation analysis was used to model the pathways of effects. Neither of two attempted experimental manipulations of apophenia, nor self-reported levels of apophenia, had a significant effect on proportions of maximizing choices. However, the use of strategy over intuition proved a consistent predictor of maximizing, across all experimental conditions. A parallel analysis was conducted to assess the effect of controlling for individual variance in perceptions of reward contingencies. Although this analysis suggested that apophenia did increase probability matching in the standard task preparation, this effect was found to result from an unforeseen relationship between self-reported apophenia and perceived reward probabilities. A Win-stay Lose-shift (WSLS) analysis indicated no reliable relationship between WSLS and either intuition or strategy use

Capturing richer information: On establishing the validity of an interval-valued survey response mode

Obtaining quantitative survey responses that are both accurate and informative is crucial to a wide range of fields. Traditional and ubiquitous response formats such as Likert and visual analogue scales require condensation of responses into discrete or point values—but sometimes a range of options may better represent the correct answer. In this paper, we propose an efficient interval-valued response mode, whereby responses are made by marking an ellipse along a continuous scale. We discuss its potential to capture and quantify valuable information that would be lost using conventional approaches, while preserving a high degree of response efficiency. The information captured by the response interval may represent a possible response range—i.e., a conjunctive set, such as the real numbers between 3 and 6. Alternatively, it may reflect uncertainty in respect to a distinct response—i.e., a disjunctive set, such as a confidence interval. We then report a validation study, utilizing our recently introduced open-source software (DECSYS), to explore how interval-valued survey responses reflect experimental manipulations of several factors hypothesised to influence interval width, across multiple contexts. Results consistently indicate that respondents used interval widths effectively, and subjective participant feedback was also positive. We present this as initial empirical evidence for the efficacy and value of interval-valued response capture. Interestingly, our results also provide insight into respondents’ reasoning about the different aforementioned types of intervals—we replicate a tendency towards overconfidence for those representing epistemic uncertainty (i.e., disjunctive sets), but find intervals representing inherent range (i.e., conjunctive sets) to be well-calibrated

Healthy cats tolerate long-term daily feeding of Cannabidiol

Cannabidiol (CBD)-containing products are widely commercially available for companion animals, mirroring popularity in human use. Although data on the safety and efficacy of long-term oral supplementation are increasing in dogs, evidence remains lacking in cats. The purpose of these studies was to address gaps in the knowledge around the long-term suitability and tolerance of a tetrahydrocannabinol (THC)-free CBD distillate in clinically healthy cats. The studies were randomized, blinded, and placebo-controlled. The first study supplemented cats with either a placebo oil (n = 10) or with 4 mg/kg body weight (BW) CBD in placebo oil (n = 9) daily, with a meal, for 4 weeks. The concentration of CBD in plasma was measured over 4 h at d0 (first dose) and again at d14 (after 2 weeks of daily dosing). The second study supplemented cats daily with either placebo oil (n = 10) or 4 mg/kg BW CBD in placebo oil (n = 10) for a period of 26 weeks. A comprehensive suite of physiological health measures was performed throughout the study at baseline (week 0) and after 4, 10, 18, and 26 weeks of feeding, followed by a 4-week washout sample (week 30). Postprandial plasma CBD time course data, at both d0 and d14, showed a peak plasma CBD concentration at 2 h after the dose. This peak was 251 (95% CI: 108.7, 393.4) and 431 (95% CI, 288.7, 573.4) ng/mL CBD at d0 and d14, respectively, and the area under the curve concentration was higher by 91.5 (95% CI, 33.1, 149.9) ng-h/mL after 2 weeks of supplementation (p = 0.002). While in the first study the CBD group displayed increased alanine aminotransferase (ALT; 68.7 (95% CI, 43.23, 109.2) U/L) at week 4 compared to the placebo control group [1.44-fold increase (95% CI, 0.813, 2.54)], statistical equivalence (at 2-fold limits) was found for ALT across the duration of the second, long-term study. All other biochemistry and hematology data showed no clinically significant differences between supplement groups. Data presented here suggest that a THC-free, CBD distillate fed at a dose of 4 mg/kg BW was absorbed into plasma and well tolerated by healthy cats when supplemented over a period of 26 weeks

A combined behavioural and electrophysiological examination of the faulty foraging theory of probability matching

Given a repeated choice between two or more options with fixed, independent and identically distributed reward probabilities, overall pay-offs can be maximized by the exclusive selection of the option with the greatest likelihood of reward. The tendency to match response proportions to reward contingencies is suboptimal. Nevertheless, this behaviour is well documented. This thesis had two core objectives. First, it was aimed to ascertain the relative contributions of several existing accounts of probability matching in determining choice behaviour, particularly regarding the maximization versus diversification of choices. These accounts include failed pattern matching, driven by apophenia, and a heuristic-driven response that can be overruled with sufficient deliberation. Second, to then further address potential mechanisms underlying whichever factor was found to make the most substantive contribution to choice behaviour, through the combined application of behavioural and electrophysiological methods. Over a series of behavioural studies, the use of strategy over intuition proved to be the most consistent and substantial predictor of maximizing choices, in robust support of the heuristic account. Given this finding, the question emerges of why probability matching is the dominant intuitive response. One possibility is that matching represents the overextension of an evolutionarily stable foraging strategy, an account termed the ‘Faulty Foraging Theory’. A simple simulated foraging task was designed to assess choice behaviour when reward schedules incorporate the factor of natural resource accumulation and depletion. The contrast in choice behaviour on this task with the standard probability matching preparation was consistent with the Faulty Foraging model. A series of electrophysiological studies were then conducted, in an attempt to uncover the putative illusory internal representation of reward accumulation on the standard task, which could drive suboptimal diversification of choices. This was ultimately unsuccessful. However, further corroborating electrophysiological evidence was obtained for the heuristic account, in the form of characteristic patterns of prefrontal activity relating to maximizing vs. diversification of choices