Driving with Style: Inverse Reinforcement Learning in General-Purpose Planning for Automated Driving

Behavior and motion planning play an important role in automated driving. Traditionally, behavior planners instruct local motion planners with predefined behaviors. Due to the high scene complexity in urban environments, unpredictable situations may occur in which behavior planners fail to match predefined behavior templates. Recently, general-purpose planners have been introduced, combining behavior and local motion planning. These general-purpose planners allow behavior-aware motion planning given a single reward function. However, two challenges arise: First, this function has to map a complex feature space into rewards. Second, the reward function has to be manually tuned by an expert. Manually tuning this reward function becomes a tedious task. In this paper, we propose an approach that relies on human driving demonstrations to automatically tune reward functions. This study offers important insights into the driving style optimization of general-purpose planners with maximum entropy inverse reinforcement learning. We evaluate our approach based on the expected value difference between learned and demonstrated policies. Furthermore, we compare the similarity of human driven trajectories with optimal policies of our planner under learned and expert-tuned reward functions. Our experiments show that we are able to learn reward functions exceeding the level of manual expert tuning without prior domain knowledge.Comment: Appeared at IROS 2019. Accepted version. Added/updated footnote, minor correction in preliminarie

Emotion, deliberation, and the skill model of virtuous agency

A recent skeptical challenge denies deliberation is essential to virtuous agency: what looks like genuine deliberation is just a post hoc rationalization of a decision already made by automatic mechanisms (Haidt 2001; Doris 2015). Annas’s account of virtue seems well-equipped to respond: by modeling virtue on skills, she can agree that virtuous actions are deliberation-free while insisting that their development requires significant thought. But Annas’s proposal is flawed: it over-intellectualizes deliberation’s developmental role and under-intellectualizes its significance once virtue is acquired. Doing better requires paying attention to a distinctive form of anxiety—one that functions to engage deliberation in the face of decisions that automatic mechanisms alone cannot resolve

How cognitive and reactive fear circuits optimize escape decisions in humans

Flight initiation distance (FID), the distance at which an organism flees from an approaching threat, is an ecological metric of cost–benefit functions of escape decisions. We adapted the FID paradigm to investigate how fast- or slow-attacking “virtual predators” constrain escape decisions. We show that rapid escape decisions rely on “reactive fear” circuits in the periaqueductal gray and midcingulate cortex (MCC), while protracted escape decisions, defined by larger buffer zones, were associated with “cognitive fear” circuits, which include posterior cingulate cortex, hippocampus, and the ventromedial prefrontal cortex, circuits implicated in more complex information processing, cognitive avoidance strategies, and behavioral flexibility. Using a Bayesian decision-making model, we further show that optimization of escape decisions under rapid flight were localized to the MCC, a region involved in adaptive motor control, while the hippocampus is implicated in optimizing decisions that update and control slower escape initiation. These results demonstrate an unexplored link between defensive survival circuits and their role in adaptive escape decisions

The Fear Management Model: Building an Integrative Fear Appeal Theory through System Dynamics

[[abstract]]This paper attempts to refine the Extended Parallel Process Model by adding the notion of hope to highlight the significant role of fear in fear appeals. Using System Dynamics modeling methods to reformulate the key constructs and integrate the ideas drawn from theories of multiple disciplines, the relationship between danger control and fear control processes are modified. Accordingly, the Fear Management Model is devised to fix the flaws and resolve the major unanswered questions in fear appeal literatures. Moreover, the implications for helping resistant audiences to pursue adaptive behaviors are discussed. Fourteen propositions are proposed for guiding hypothesis development in future research.[[notice]]補正完

Information Security as Strategic (In)effectivity

Security of information flow is commonly understood as preventing any information leakage, regardless of how grave or harmless consequences the leakage can have. In this work, we suggest that information security is not a goal in itself, but rather a means of preventing potential attackers from compromising the correct behavior of the system. To formalize this, we first show how two information flows can be compared by looking at the adversary's ability to harm the system. Then, we propose that the information flow in a system is effectively information-secure if it does not allow for more harm than its idealized variant based on the classical notion of noninterference

Ecosystem complexity, firm learning and survival: UK evidence on intra-industry age and size diversity as exit hazards

Firm age or size diversity in an industry is taken for granted but its implications for industry evolution and firm survival have remained below the radars of empirical research. We address this knowledge gap by drawing on an interdisciplinary theoretical framework informed by theoretical biology, organizational ecology and industrial organisation. We hypothesize that firms in more diverse industries are more likely to exit as a result of rugged fitness distributions where a global fitness optimum is less likely to emerge. We also hypothesize that investment in research and development (R&D) may counterbalance the adverse effect of diversity on survival by enabling the firm to engage in active learning about its market and technology niches. Evidence from discrete-time hazard estimators and an unbalanced panel dataset of 35,136 R&D-active UK firms lend support to these hypotheses. The findings remain robust to: (i) a battery of sensitivity checks, including step-wise estimations, different diversity measures and various firm cohorts; (ii) control for frailty and for a wide range of firm, industry, and macroeconomic factors considered in the survival literature; and (iii) taking account of direct effects of age, size and R&D intensity

Revisiting the form and function of conflict: Neurobiological, psychological, and cultural mechanisms for attack and defense within and between groups

Conflict can profoundly affect individuals and their groups. Oftentimes, conflict involves a clash between one side seeking change and increased gains through victory and the other side defending the status quo and protecting against loss and defeat. However, theory and empirical research largely neglected these conflicts between attackers and defenders, and the strategic, social, and psychological consequences of attack and defense remain poorly understood. To fill this void, we model (1) the clashing of attack and defense as games of strategy and reveal that (2) attack benefits from mismatching its target's level of defense, whereas defense benefits from matching the attacker's competitiveness. This suggests that (3) attack recruits neuroendocrine pathways underlying behavioral activation and overconfidence, whereas defense invokes neural networks for behavioral inhibition, vigilant scanning, and hostile attributions; and that (4) people invest less in attack than defense, and attack often fails. Finally, we propose that (5) in intergroup conflict, out-group attack needs institutional arrangements that motivate and coordinate collective action, whereas in-group defense benefits from endogenously emerging in-group identification. We discuss how games of attack and defense may have shaped human capacities for prosociality and aggression, and how third parties can regulate such conflicts and reduce their waste. Keywords: behavioral game theory; biobehavioral approach–avoidance; coevolution of prosociality and aggression; conflict; conflict intervention; cultural institutions; intergroup relations; psychological adaptations

The Human Brain Encodes Event Frequencies While Forming Subjective Beliefs

To make adaptive choices, humans need to estimate the probability of future events. Based on a Bayesian approach, it is assumed that probabilities are inferred by combining a priori, potentially subjective, knowledge with factual observations, but the precise neurobiological mechanism remains unknown. Here, we study whether neural encoding centers on subjective posterior probabilities, and data merely lead to updates of posteriors, or whether objective data are encoded separately alongside subjective knowledge. During fMRI, young adults acquired prior knowledge regarding uncertain events, repeatedly observed evidence in the form of stimuli, and estimated event probabilities. Participants combined prior knowledge with factual evidence using Bayesian principles. Expected reward inferred from prior knowledge was encoded in striatum. BOLD response in specific nodes of the default mode network (angular gyri, posterior cingulate, and medial prefrontal cortex) encoded the actual frequency of stimuli, unaffected by prior knowledge. In this network, activity increased with frequencies and thus reflected the accumulation of evidence. In contrast, Bayesian posterior probabilities, computed from prior knowledge and stimulus frequencies, were encoded in bilateral inferior frontal gyrus. Here activity increased for improbable events and thus signaled the violation of Bayesian predictions. Thus, subjective beliefs and stimulus frequencies were encoded in separate cortical regions. The advantage of such a separation is that objective evidence can be recombined with newly acquired knowledge when a reinterpretation of the evidence is called for. Overall this study reveals the coexistence in the brain of an experience-based system of inference and a knowledge-based system of inference

Shady Strategic Behavior: Recognizing Strategic Followership of Dark Triad Followers

The importance of strategic behavior in organizations has long been recognized. However, so far the literature has primarily focused on leaders’ strategic behavior, largely ignoring followers’ strategic behavior. In the present paper, we take a follower trait perspective to strategic follower behavior, specifically focusing on how followers’ Dark Triad traits (i.e., narcissism, Machiavellianism, and psychopathy) influence their strategic behavior. We argue that Dark Triad related strategic follower behavior is likely to have negative effects for fellow organizational members and the organization as a whole. We also present ‘red flag’ behaviors that may signal followers' tendencies to engage in shady strategic behaviors. Then, we put forward factors that may mitigate or increase the occurrence of shady strategic behaviors of followers scoring high on Dark Triad traits, focusing especially on leader attributes and specifics of the organizational context. Finally, we discuss if and how followers’ Dark Triad traits could benefit the organization, and highlight emerging issues in research on strategic follower behavior