Propagation of singularities around a Lagrangian submanifold of radial points

In this work we study the wavefront set of a solution u to Pu = f, where P is a pseudodifferential operator on a manifold with real-valued homogeneous principal symbol p, when the Hamilton vector field corresponding to p is radial on a Lagrangian submanifold contained in the characteristic set of P. The standard propagation of singularities theorem of Duistermaat-Hormander gives no information at the Lagrangian submanifold. By adapting the standard positive-commutator estimate proof of this theorem, we are able to conclude additional regularity at a point q in this radial set, assuming some regularity around this point. That is, the a priori assumption is either a weaker regularity assumption at q, or a regularity assumption near but not at q. Earlier results of Melrose and Vasy give a more global version of such analysis. Given some regularity assumptions around the Lagrangian submanifold, they obtain some regularity at the Lagrangian submanifold. This paper microlocalizes these results, assuming and concluding regularity only at a particular point of interest. We then proceed to prove an analogous result, useful in scattering theory, followed by analogous results in the context of Lagrangian regularity.Comment: 39 pages, 4 figure

What's up with WAC? Archaeology and 'engagement' in a globalized world

The year 2011 marks the twenty-fifth anniversary of the World Archaeological Congress (WAC). WAC marked a bold intervention in the politics of knowledge in archaeology in the context of the mid-1980s. But how has it fared in contemporary worlds of practice? In this paper, two senior WAC members take a close and critical look at the changing fortunes, meanings, and contexts of the organization. At its centre, is an account of the controversial meeting between the WAC Executive and Rio Tinto Limited, the mining multinational, in Melbourne in 2007. Other parts of the paper engage with notions of the Indigenous, and discuss the assumptions informing the WAC programme Archaeologists Without Borders. Framed as a challenge, the paper invites response and commentary, as a way of opening debate which allows us to envisage alternative futures for the discipline, beyond the banal prospect of 'Archaeology Inc.'.Fil: Shepherd, Nick. University of Cape Town; SudáfricaFil: Haber, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Catamarca; Argentin

Counter-practices of global life: A response to Claire Smith

We had hoped for a substantive response around the argument presented in ‘What’s up with WAC?’, instead Claire Smith has responded with a list of what she styles as ‘errors of fact and errors of representation’. Nevertheless, we thank her for the attention with which she has read our paper, and we look forward to the ‘more discursive response’ which she indicates will be forthcoming. A careful reading of Smith’s response yields fi ve points at which she correctly identifi es errors of fact in our paper. So, for the sake of the record, and in the interests of getting this over with, here goes: • It is correct that most of the books distributed through the Global Libraries Programme are new rather than second-hand; • It is correct that Colombia’s bid for WAC-6 competed against Ireland rather than Jamaica, after Jamaica’s bid had been rejected; • It is correct that the room of the WAC/ Rio Tinto meeting in Melbourne was not — literally — ‘full of lawyers’. Rather, the tone of the proceedings was legalistic, and signifi cant Rio Tinto input came from ‘community agreements’ and ‘community relations’ specialists with legal training; • The sentence ‘WAC would become an archaeological/scientifi c organization whose salaried offi ce holders were paid by Rio Tinto’, should read ‘WAC would become an archaeological/scientifi c organization whose salaried secretariat was paid by Rio Tinto’; • The countries proposed for the WAC/ Rio Tinto try-out were not Cameroon and Argentina as stated, but Gabon and Argentina.Fil: Shepherd, Nick. University of Cape Town; SudáfricaFil: Haber, Alejandro. Universidad Nacional de Catamarca. Escuela de Arqueología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Catamarca. Universidad Nacional de Catamarca. Centro de Investigaciones y Transferencia de Catamarca; Argentin

Curious Replay for Model-based Adaptation

Agents must be able to adapt quickly as an environment changes. We find that existing model-based reinforcement learning agents are unable to do this well, in part because of how they use past experiences to train their world model. Here, we present Curious Replay -- a form of prioritized experience replay tailored to model-based agents through use of a curiosity-based priority signal. Agents using Curious Replay exhibit improved performance in an exploration paradigm inspired by animal behavior and on the Crafter benchmark. DreamerV3 with Curious Replay surpasses state-of-the-art performance on Crafter, achieving a mean score of 19.4 that substantially improves on the previous high score of 14.5 by DreamerV3 with uniform replay, while also maintaining similar performance on the Deepmind Control Suite. Code for Curious Replay is available at https://github.com/AutonomousAgentsLab/curiousreplayComment: Accepted at ICML 2023. Website at https://sites.google.com/view/curious-repla

¿Qué pasa con el wac? arqueología y “compromiso” en un mundo globalizado

The year 2011 marks the twenty-fifth anniversary of the World Archaeological Congress. WAC marked a bold intervention in the politics of knowledge in archaeology in the context of the But how has it fared in contemporary worlds of practice? In this two senior WAC members take a close and critical look at the fortunes, meanings and contexts of the organisation. At its centre, is an account of the meeting between the WAC and Rio Tinto Limited, the mining multinational, in Melbourne in 2007. Other parts of the paper engage with notions of the indigenous, and discuss the assumptions informing the WAC program Without Borders. Framed as a challenge, the paper invites response and commentary, as a way of opening debate which allows us to envisage alternative futures for the discipline, beyond the banal prospect of “Archaeology Inc.”El año 2011 marca el vigésimo quinto  del Congreso Arqueológico  (WAC, por sus siglas en inglés).  WAC marcó una audaz intervención  la política del en el contexto de mediados de los años ochentas. Más, ¿cómo le fue en los mundos contemporáneos de la ? En este artículo, dos antiguos  del WAC adoptan una mirada  y crítica sobre las cambiantes , significados y contextos de.Centralmente, es un relato  controvertido encuentro entre el Ejecutivo  WAC y Rio Tinto minera, en Melbourne en 2007. Otras partes del artículo nociones de lo indígena, y discuten  supuestos que integran el programa del WAC Sin Fronteras”.  como un desafío, este artículo  respuestas y comentarios,  una de abrir un debate que  permita entrever futuros alternativos  la disciplina, más allá de la banal  de una “Arqueología Ltda.

Parsel: A (De-)compositional Framework for Algorithmic Reasoning with Language Models

Despite recent success in large language model (LLM) reasoning, LLMs struggle with hierarchical multi-step reasoning tasks like generating complex programs. For these tasks, humans often start with a high-level algorithmic design and implement each part gradually. We introduce Parsel, a framework enabling automatic implementation and validation of complex algorithms with code LLMs, taking hierarchical function descriptions in natural language as input. We show that Parsel can be used across domains requiring hierarchical reasoning, including program synthesis, robotic planning, and theorem proving. We show that LLMs generating Parsel solve more competition-level problems in the APPS dataset, resulting in pass rates that are over 75% higher than prior results from directly sampling AlphaCode and Codex, while often using a smaller sample budget. We also find that LLM-generated robotic plans using Parsel as an intermediate language are more than twice as likely to be considered accurate than directly generated plans. Lastly, we explore how Parsel addresses LLM limitations and discuss how Parsel may be useful for human programmers.Comment: new quantitative detail

Emergence of Structured Behaviors from Curiosity-Based Intrinsic Motivation

Infants are experts at playing, with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals. We seek to replicate some of these abilities with a neural network that implements curiosity-driven intrinsic motivation. Using a simple but ecologically naturalistic simulated environment in which the agent can move and interact with objects it sees, the agent learns a world model predicting the dynamic consequences of its actions. Simultaneously, the agent learns to take actions that adversarially challenge the developing world model, pushing the agent to explore novel and informative interactions with its environment. We demonstrate that this policy leads to the self-supervised emergence of a spectrum of complex behaviors, including ego motion prediction, object attention, and object gathering. Moreover, the world model that the agent learns supports improved performance on object dynamics prediction and localization tasks. Our results are a proof-of-principle that computational models of intrinsic motivation might account for key features of developmental visuomotor learning in infants.Comment: 6 pages, 5 figure

Examining the Potential and Pitfalls of ChatGPT in Science and Engineering Problem-Solving

The study explores the capabilities of OpenAI's ChatGPT in solving different types of physics problems. ChatGPT (with GPT-4) was queried to solve a total of 40 problems from a college-level engineering physics course. These problems ranged from well-specified problems, where all data required for solving the problem was provided, to under-specified, real-world problems where not all necessary data were given. Our findings show that ChatGPT could successfully solve 62.5% of the well-specified problems, but its accuracy drops to 8.3% for under-specified problems. Analysis of the model's incorrect solutions revealed three distinct failure modes: 1) failure to construct accurate models of the physical world, 2) failure to make reasonable assumptions about missing data, and 3) calculation errors. The study offers implications for how to leverage LLM-augmented instructional materials to enhance STEM education. The insights also contribute to the broader discourse on AI's strengths and limitations, serving both educators aiming to leverage the technology and researchers investigating human-AI collaboration frameworks for problem-solving and decision-making.Comment: 12 pages, 2 figure