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I'm currently preparing for graduate study exploring natural and artificial intelligence, particularly informatics applied to neuroscience & cognitive science, information processing, and the engineering that underpins decision making and comprehension. Active Projects: Orthogonal Research & Education Lab: Representational Brains and Phenotypes Team; DevoWorm; FrontierMap, Cognition Futures
October 2020 - present
Orthogonal Research and Education Lab
- Project Manager
January 2020 - present
April 2019 - present
Orthogonal Research and Education Lab
- Laboratory Manager
We propose a new way to quantitatively characterize information: Gibsonian Information (GI). This framework is relevant to both the study of cognitive agents and single cell systems that exhibit cognitive behaviors. GI provides a means to characterize how agents extract information from direct perceptual signals. This differs from existing informat...
Artificial Intelligence (AI) systems based solely on neural networks or symbolic computation present a representational complexity challenge. While minimal representations can produce behavioral outputs like locomotion or simple decision-making, more elaborate internal representations might offer a richer variety of behaviors. We propose that these...
In the present paper we will approach enactivism from the perspective of internal regulation: while the environment shapes the organism, it is also true that organisms have complex internal states with regulatory machinery with a set of continuous phenotype-environment interactions. The aim of the present paper is to provide a visual means to analy...
March 24 Afternoon breakout session. Slides for ~3 minute flash talk. An overview of projects within Cognition Futures and orthogonal Research and Education Lab.
While Artificial Neural Networks (ANNs) have yielded impressive results in the realm of simulated intelligent behavior, it is important to remember that they are but sparse approximations of Biological Neural Networks (BNNs). We go beyond comparison of ANNs and BNNs to introduce principles from BNNs that might guide the further development of ANNs...
Extended Abstract submission to ALIFE 2021. Abstract: Where should researchers focus their efforts within the vast frontier of civilization's increasing virtual, augmented, and enhanced manner of living? We offer Mapping Cyborg Cognitive Futures as a set of lenses to help identify fruitful areas of investigation, holistic context, and ethical & d...
Does embryonic development exhibit characteristic temporal features? This is apparent in evolution, where evolutionary change has been shown to occur in bursts of activity. Using two animal models (Nematode, Caenorhabditis elegans and Zebrafish, Danio rerio) and simulated data, we demonstrate that temporal heterogeneity exists in embryogenesis at t...
We present a framework for meta-brain models, or hybrid models that capture multiple aspects of developmental neuro-biology and behavior. A developmentally-inspired embodied learning agent architecture is combined with a contextually-explicit representational layer to form a complex artificial nervous system. The architectural description is summar...
We present a framework for meta-brain models, or hybrid models that capture multiple aspects of developmental neurobiology and behavior. A developmentally-inspired embodied learning agent architecture is combined with a contextually-explicit representational layer to form a complex artificial nervous system. The architectural description is summari...
A brief summary of key themes about tech, ethics, and data creation / analyzing that came up during ICLR 2020 and CSV conf v5.
We discuss challenges and opportunities across industries regarding ethical issues in the use and development of AI and big data. We draw from personal experience and interviews in academia, information technology, cybersecurity, social work, entrepreneurship, research and law. Findings are compared to projections of technology evolution within tho...
The ability to formalize problems in a quantitative manner is the key to predictive power. We characterize a lack of formality as unruliness, relate unruliness as a property of un(3) (undecidability, uncomputability, and unpredictability), and define a class of problems which even when well-posed remain highly informal in nature. Despite this lack...
An overview of the challenges in AI + Law.
ACM Special Interest Group in Artificial Intelligence (SIGAI) Student Essay Contest 2019 [Submitted] Abstract: We put into action calls for an interdisciplinary approach to AI Ethics by collaborating internationally as a STEM and Law student. We discuss micro- and macro-level perspectives on creation and legislation of AI systems and technology. A...
Track: AI for Human-Robot Interaction Socially Intelligent HRI Systems: AI systems that are able to comprehend social dynamics between multiple human speakers Presenting: Analyses of interaction via a social context label, engagement, with source data of real-life relationships and affective emotion display. Foundation for future work in quantif...
What has changed since this Pezzulo et al Paper?