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Subjective Experience (SE) is part of the ancient mind-body problem, which continues to be one of deepest mysteries of science. Despite major advances in many fields, there is still no plausible causal link between SE and its realization in the body. The core issue is the incompatibility of objective (3rd person) public science with subjective (1st person) private experience. Any scientific approach to SE assumes that it arose from extended evolutionary processes and that examining evolutionary history should help us understand it. While the core mystery remains, converging evidence from theoretical, experimental, and computational studies yields strong constraints on SE and some suggestions for further research. All animals confront many of the same fitness challenges. They all need some kind of internal model to relate their life goals and actionable sensed information to action. We understand the evolution of the bodily aspects of human perception and emotion, but not the SE. The first evolutionary evidence for SE appears in vertebrates and much of its neural substrate and simulation mechanism is preserved in mammals and humans. People exhibit the same phenomena, but there are remaining mysteries of everyday experience that are demonstrably incompatible with current neuroscience. In spite of this limitation, there is considerable progress on understanding the role of SE in the success of prostheses., Comment: 49 pages 5 figures. This 7/22/2021 version preserves all the content of the previous version and adds additional discussion (in italics). It also includes several new references to connect with current literature. A companion arXiv article has also been updated

The ancient mind/body problem continues to be one of deepest mysteries of science and of the human spirit. Despite major advances in many fields, there is still no plausible link between subjective experience (qualia) and its realization in the body. This paper outlines some of the elements of a rigorous science of mind (SoM) - key ideas include scientific realism of mind, agnostic mysterianism, careful attention to language, and a focus on concrete (touchstone) questions and results. A core suggestion is to focus effort on the (still mysterious) mapping from neural activity to subjective experience., Comment: 18 pages and 1 Figure. The ancient mind/body remains a scientific and existential mystery. This article develops a methodology for an incremental Science of Mind and describes some ongoing prospects and successes. Updates include additional phenomena, including emotions,and several more references. A major addition is a postulated general (mysterious) brain-mind mapping

Actions may not proceed as planned; they may be interrupted, resumed or overridden. This is a challenge to handle in a natural language understanding system. We describe extensions to an existing implementation for the control of autonomous systems by natural language, to enable such systems to handle incoming language requests regarding actions. Language Communication with Autonomous Systems (LCAS) has been extended with support for X-nets, parameterized executable schemas representing actions. X-nets enable the system to control actions at a desired level of granularity, while providing a mechanism for language requests to be processed asynchronously. Standard semantics supported include requests to stop, continue, or override the existing action. The specific domain demonstrated is the control of motion of a simulated robot, but the approach is general, and could be applied to other domains., Comment: 6 pages, 8 figures. Updated with PIPE citations

Science is a crowning glory of the human spirit and its applications remain our best hope for social progress. But there are limitations to current science and perhaps to any science. The general mind-body problem is known to be intractable and currently mysterious. This is one of many deep problems that are universally agreed to be beyond the current purview of Science, including quantum phenomena, etc. But all of these famous unsolved problems are either remote from everyday experience (entanglement, dark matter) or are hard to even define sharply (phenomenology, consciousness, etc.). An updated summary of this work has been published as: Feldman, J. (2022). Computation, perception, and mind. Behavioral and Brain Sciences, 45, E48. doi:10.1017/S0140525X21001886 A more readable, open access, version is: https://escholarship.org/uc/item/6cs78450, Comment: This 3/27/2022 revision retains all the original text but adds new comments (in italics) There are several new references, connecting with current research

We develop a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of natural language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art.