Emergence in genetic programming:let's exploit it!

Banzhaf explores the concept of emergence and how and where it happens in genetic programming [1]. Here we consider the question: what shall we do with it? We argue that given our ultimate goal to produce genetic programming systems that solve new and difficult problems, we should take advantage of emergence to get closer to this goal

Study the Effects of Multilevel Selection in Multi-Population Cultural Algorithm

This is a study on the effects of multilevel selection (MLS) theory in optimizing numerical functions. Based on this theory, a new architecture for Multi-Population Cultural Algorithm is proposed which incorporates a new multilevel selection framework (ML-MPCA). The approach used in this paper is based on biological group selection theory that states natural selection acts collectively on all the members of a given group. The effects of cooperation are studied using n-player prisoner’s dilemma. In this game, N individuals are randomly divided into m groups and individuals independently choose to be either cooperator or defector. A two-level selection process is introduced namely within group selection and between group selection. Individuals interact with the other members of the group in an evolutionary game that determines their fitness. The principal idea behind incorporating this multilevel selection model is to avoid premature convergence and to escape from local optima and for better exploration of the search space. We test our algorithm using the CEC 2015 expensive benchmark functions to evaluate its performance. These problems are a set of 15 functions which includes varied function categories. We show that our proposed algorithm improves solution accuracy and consistency. For 10 dimensional problems, the proposed method has 8 out 15 better results and for 30-dimensional problems we have 11 out of 15 better results when compared to the existing algorithms. The proposed model can be extended to more than two levels of selection and can also include migration

How Biology Became Social and What It Means for Social Theory

In this paper I first offer a systematic outline of a series of conceptual novelties in the life-sciences that have favoured, over the last three decades, the emergence of a more social view of biology. I focus in particular on three areas of investigation: (1) technical changes in evolutionary literature that have provoked a rethinking of the possibility of altruism, morality and prosocial behaviours in evolution; (2) changes in neuroscience, from an understanding of the brain as an isolated data processor to the ultrasocial and multiply connected social brain of contemporary neuroscience; and (3) changes in molecular biology, from the view of the gene as an autonomous master of development to the ‘reactive genome’ of the new emerging field of molecular epigenetics. In the second section I reflect on the possible implications for the social sciences of this novel biosocial terrain and argue that the postgenomic language of extended epigenetic inheritance and blurring of the nature/nurture boundaries will be as provocative for neo-Darwinism as it is for the social sciences as we have known them. Signs of a new biosocial language are emerging in several social-science disciplines and this may represent an exciting theoretical novelty for twenty-first social theory

Distinguishing Family from Friends

Kinship and friendship are key human relationships. Increasingly, data suggest that people are not less altruistic toward friends than close kin. Some accounts suggest that psychologically we do not distinguish between them; countering this is evidence that kinship provides a unique explanatory factor. Using the Implicit Association Test, we examined how people implicitly think about close friends versus close kin in three contexts. In Experiment 1, we examined generic attitudinal dispositions toward friends and family. In Experiment 2, attitude similarity as a marker of family and friends was examined, and in Experiments 3 and 4, strength of in-group membership for family and friends was examined. Findings show that differences exist in implicit cognitive associations toward family and friends. There is some evidence that people hold more positive general dispositions toward friends, associate attitude similarity more with friends, consider family as more representative of the in-group than friends, but see friends as more in-group than distant kin

Identifying Patterns in Course-Taking that Predict Student Leaving: A Comparison of Different Predictive Algorithms

Higher education institutions continue to face the problem of student attrition, which in turn impacts graduation rates overall. This has numerous drawbacks not only at the university or student levels but has far-reaching influences on society itself (Schuh & Topf, 2012). Although much research has investigated various factors that contribute towards attrition, on average only 40.3% of college students are found to complete their degrees (ACT, 2008). Despite an attempt to better understand the role different kinds of predictors have towards student success (Lotkowski, Robbins, & Noeth, 2004), limited research has assessed to what extent course information adds incremental variability towards predictive modeling of student retention. Lewis and Terry (2016) have investigated the application of multi-level modeling toward such predictors, while data mining techniques have been used sparingly to support the use of differing predictors. For this study, a method of data mining relatively new to the field of educational literature is contrasted with a hierarchically-based statistical approach to support in determining whether any significant course patterns can lead to improved student retention outcomes. Results from the analysis may provide insight into models that contain greater predictive accuracy, with long-term benefits into course placement as more effective advising is applied. Over time, any improved placement is expected to yield positive effects for students and the university as a whole. Keywords: student retention, data mining, symbolic regression, logistic regression, hierarchical analysis, multilevel modeling, statistical techniques, exploratory analysis, area under curve, AU

Blocking D2/D3 dopamine receptors in male participants increases volatility of beliefs when learning to trust others

The ability to learn about other people is crucial for human social functioning. Dopamine has been proposed to regulate the precision of beliefs, but direct behavioural evidence of this is lacking. In this study, we investigate how a high dose of the D2/D3 dopamine receptor antagonist sulpiride impacts learning about other people’s prosocial attitudes in a repeated Trust game. Using a Bayesian model of belief updating, we show that in a sample of 76 male participants sulpiride increases the volatility of beliefs, which leads to higher precision weights on prediction errors. This effect is driven by participants with genetically conferred higher dopamine availability (Taq1a polymorphism) and remains even after controlling for working memory performance. Higher precision weights are reflected in higher reciprocal behaviour in the repeated Trust game but not in single-round Trust games. Our data provide evidence that the D2 receptors are pivotal in regulating prediction error-driven belief updating in a social context

Open Problems in (Hyper)Graph Decomposition

Large networks are useful in a wide range of applications. Sometimes problem instances are composed of billions of entities. Decomposing and analyzing these structures helps us gain new insights about our surroundings. Even if the final application concerns a different problem (such as traversal, finding paths, trees, and flows), decomposing large graphs is often an important subproblem for complexity reduction or parallelization. This report is a summary of discussions that happened at Dagstuhl seminar 23331 on "Recent Trends in Graph Decomposition" and presents currently open problems and future directions in the area of (hyper)graph decomposition