Matthias Scheutz

Matthias Scheutz
Tufts University | Tufts · Department of Computer Science

Ph.D. Ph.D.

About

451
Publications
77,959
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7,034
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Introduction
Matthias iScheutz s currently a full professor of computer and cognitive science in the Department of Computer Science at Tufts University, and Senior Gordon Faculty Fellow in the School of Engineering at Tufts where he also directs the Human-Robot Interaction Laboratory. He has over 300 peer-reviewed publications in artificial intelligence, artificial life, agent-based computing, natural language processing, cognitive modeling, robotics, human-robot interaction and foundations of cognitive science. His current research and teaching interests include multi-scale agent-based models of social behavior and complex cognitive and affective autonomous robots with natural language and ethical reasoning capabilities for natural human-robot interaction.
Additional affiliations
September 2010 - present
Tufts University

Publications

Publications (451)
Preprint
Full-text available
In this paper, we propose a novel domain generalization (DG) framework based on a new upper bound to the risk on the unseen domain. Particularly, our framework proposes to jointly minimize both the covariate-shift as well as the concept-shift between the seen domains for a better performance on the unseen domain. While the proposed approach can be...
Preprint
We propose RAPid-Learn: Learning to Recover and Plan Again, a hybrid planning and learning method, to tackle the problem of adapting to sudden and unexpected changes in an agent's environment (i.e., novelties). RAPid-Learn is designed to formulate and solve modifications to a task's Markov Decision Process (MDPs) on-the-fly and is capable of exploi...
Preprint
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In order for artificial agents to perform useful tasks in changing environments, they must be able to both detect and adapt to novelty. However, visual novelty detection research often only evaluates on repurposed datasets such as CIFAR-10 originally intended for object classification. This practice restricts novelties to well-framed images of dist...
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As AI-enabled robots enter the realm of healthcare and caregiving, it is important to consider how they will address the dimensions of care and how they will interact not just with the direct receivers of assistance, but also with those who provide it (e.g., caregivers, healthcare providers, etc.). Caregiving in its best form addresses challenges i...
Preprint
Full-text available
As AI-enabled robots enter the realm of healthcare and caregiving, it is important to consider how they will address the dimensions of care and how they will interact not just with the direct receivers of assistance, but also with those who provide it (e.g., caregivers, healthcare providers etc.). Caregiving in its best form addresses challenges in...
Article
As development of robots with the ability to self-assess their proficiency for accomplishing tasks continues to grow, metrics are needed to evaluate the characteristics and performance of these robot systems and their interactions with humans. This proficiency-based human-robot interaction (HRI) use case can occur before, during, or after the perfo...
Article
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Potential applications of robots in private and public human spaces have prompted the design of so-called “social robots” that can interact with humans in social settings and potentially cause humans to attach to the robots. The focus of this paper is an analysis of possible benefits and challenges arising from such human-robot attachment as report...
Article
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Language-enabled robots with moral reasoning capabilities will inevitably face situations in which they have to respond to human commands that might violate normative principles and could cause harm to humans. We believe that it is critical for robots to be able to reject such commands. We thus address the two key challenges of when and how to reje...
Article
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Attachment theory is a research area in psychology that has enjoyed decades of successful study, and has subsequently become explored in realms beyond that of the original infant-caregiver bonds. Now, attachment is studied in relation to pets, symbols (such as deities), objects, technologies, and notably for our purposes, robots. When we discuss at...
Preprint
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Invariance principle-based methods, for example, Invariant Risk Minimization (IRM), have recently emerged as promising approaches for Domain Generalization (DG). Despite the promising theory, invariance principle-based approaches fail in common classification tasks due to the mixture of the true invariant features and the spurious invariant feature...
Article
Full-text available
Understanding the spread of false or dangerous beliefs—often called misinformation or disinformation—through a population has never seemed so urgent. Network science researchers have often taken a page from epidemiologists, and modeled the spread of false beliefs as similar to how a disease spreads through a social network. However, absent from tho...
Chapter
An agent’s autonomy can be viewed as the set of physically and computationally grounded algorithms that can be performed by the agent. This view leads to two useful notions related to autonomy: behavior potential and success potential, which can be used to measure of how well an agent fulfills its potential, call fulfillment. Fulfillment and succes...
Article
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As robots begin to occupy our social spaces, touch will increasingly become part of human–robot interactions. This paper examines the impact of observing a robot touch a human on trust in that robot. In three online studies, observers watched short videos of human–robot interactions and provided a series of judgments about the robot, which either d...
Article
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Environmental psychology aims to study human behavior with regard to the environment and how psychological techniques can be used to motivate behavior change. We argue that these concepts can be applied to interactive robots designed for other tasks, which then enables them to encourage sustainability behaviors in humans. We first present a literat...
Preprint
Dialogue agents that interact with humans in situated environments need to manage referential ambiguity across multiple modalities and ask for help as needed. However, it is not clear what kinds of questions such agents should ask nor how the answers to such questions can be used to resolve ambiguity. To address this, we analyzed dialogue data from...
Preprint
For the Domain Generalization (DG) problem where the hypotheses are composed of a common representation function followed by a labeling function, we point out a shortcoming in existing approaches that fail to explicitly optimize for a term, appearing in a well-known and widely adopted upper bound to the risk on the unseen domain, that is dependent...
Preprint
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The game of monopoly is an adversarial multi-agent domain where there is no fixed goal other than to be the last player solvent, There are useful subgoals like monopolizing sets of properties, and developing them. There is also a lot of randomness from dice rolls, card-draws, and adversaries' strategies. This unpredictability is made worse when unk...
Article
Explainability has emerged as a critical AI research objective, but the breadth of proposed methods and application domains suggest that criteria for explanation vary greatly. In particular, what counts as a good explanation, and what kinds of explanation are computationally feasible, has become trickier in light of oqaque “black box” systems such...
Preprint
Full-text available
Understanding the spread of false or dangerous beliefs - so-called mis/disinformation - through a population has never seemed so urgent to many. Network science researchers have often taken a page from epidemiologists, and modeled the spread of false beliefs as similar to how a disease spreads through a social network. However, absent from those di...
Article
Full-text available
With robotics rapidly advancing, more effective human–robot interaction is increasingly needed to realize the full potential of robots for society. While spoken language must be part of the solution, our ability to provide spoken language interaction capabilities is still very limited. In this article, based on the report of an interdisciplinary wo...
Chapter
Real-word intelligent agents must be able to detect sudden and unexpected changes to their task environment and effectively respond to those changes in order to function properly in the long term. We thus isolate a set of perturbations that agents ought to address and demonstrate how task-agnostic perturbation detection and mitigation mechanisms ca...
Chapter
In the future, artificial agents are likely to make life-and-death decisions about humans. Ordinary people are the likely arbiters of whether these decisions are morally acceptable. We summarize research on how ordinary people evaluate artificial (compared to human) agents that make life-and-death decisions. The results suggest that many people are...
Preprint
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Intelligent agents that are confronted with novel concepts in situated environments will need to ask their human teammates questions to learn about the physical world. To better understand this problem, we need data about asking questions in situated task-based interactions. To this end, we present the Human-Robot Dialogue Learning (HuRDL) Corpus -...
Preprint
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Trust in human-robot interactions (HRI) is measured in two main ways: through subjective questionnaires and through behavioral tasks. To optimize measurements of trust through questionnaires, the field of HRI faces two challenges: the development of standardized measures that apply to a variety of robots with different capabilities, and the explora...
Preprint
Full-text available
Regular irradiation of indoor environments with ultraviolet C (UVC) light has become a regular task for many indoor settings as a result of COVID-19, but current robotic systems attempting to automate it suffer from high costs and inefficient irradiation. In this paper, we propose a purpose-made inexpensive robotic platform with off-the-shelf compo...
Article
Full-text available
There is a close connection between health and the quality of one’s social life. Strong social bonds are essential for health and wellbeing, but often health conditions can detrimentally affect a person’s ability to interact with others. This can become a vicious cycle resulting in further decline in health. For this reason, the social management o...
Article
Full-text available
As robots begin to enter roles in which they work closely with human teammates or peers, it is critical to understand how people trust them based on how they interpret the robot’s behavior. In this paper we investigated the interplay between trust in a robot and people’s perceptions of the robot’s emotional intelligence. We used a vignette-based me...
Conference Paper
Full-text available
Trust in human-robot interactions (HRI) is measured in two main ways: through subjective questionnaires and through behavioral tasks. To optimize measurements of trust through questionnaires, the field of HRI faces two challenges: the development of stan- dardized measures that apply to a variety of robots with different capabilities, and the explo...
Chapter
Full-text available
We present a survey of investigations of human trust in robots in the recent human-robot interaction literature. The included papers are all experimental HRI studies and were published in the years 2018 or 2019. We explore how trust is defined in these papers, as well as what types of questions about trust are investigated and how trust is being ob...
Preprint
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Symbolic planning models allow decision-making agents to sequence actions in arbitrary ways to achieve a variety of goals in dynamic domains. However, they are typically handcrafted and tend to require precise formulations that are not robust to human error. Reinforcement learning (RL) approaches do not require such models, and instead learn domain...
Article
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This paper addresses ethical challenges posed by a robot acting as both a general type of system and a discrete, particular machine. Using the philosophical distinction between “type” and “token,” we locate type-token ambiguity within a larger field of indefinite robotic identity, which can include networked systems or multiple bodies under a singl...
Chapter
Robots are increasingly embedded in human societies where they encounter human collaborators, potential adversaries, and even uninvolved by-standers. Such robots must plan to accomplish joint goals with teammates while avoiding interference from competitors, possibly utilizing bystanders to advance the robot’s goals. We propose a planning framework...
Conference Paper
Full-text available
It has been claimed that a main advantage of cognitive architectures (compared to other types of specialized robotic architectures) is that they are task-general and can thus learn to perform any task as long as they have the right perceptual and action primitives. In this paper, we provide empirical evidence for this claim by directly comparing a...
Conference Paper
Full-text available
We propose a novel approach to the problem of false belief revision in epistemic planning. Our state representations are pointed Kripke models with two binary relations over possible worlds: one representing agents' necessarily true knowledge, and one representing agents' possibly false beliefs. State transition functions maintain S5n properties in...
Article
Assistive robots are becoming an increasingly important application platform for research in robotics, AI, and HRI, as there is a pressing need to develop systems that support the elderly and people with disabilities, with a clear path to market. Yet, what remains unclear is whether current autonomous systems are already up to the task or whether a...
Article
We present two ŗelated but different cross-situational and cross-modal models of incremental word learning. M̧odel 1 is a Bayesian approach for co-learning object-word mappings and referential intention which allows for incremental learning from only a few situations w̧here the display of referents to the learning system is systematically varied. W...
Preprint
Full-text available
Autonomous robots with sophisticated capabilities can make it difficult for human instructors to assess its capabilities and proficiencies. Therefore, it is important future robots have the ability to: introspect on their capabilities and assess their task performance. Introspection allows the robot to determine what it can accomplish and self-asse...
Article
Emotions are crucial for human social interactions and thus people communicate emotions through a variety of modalities: kinesthetic (through facial expressions, body posture and gestures), auditory (the acoustic features of speech) and semantic (the content of what they say). Sometimes however, communication channels for certain modalities can be...
Preprint
Full-text available
There is a close connection between health and the quality of one's social life. Strong social bonds are essential for health and wellbeing, but often health conditions can detrimentally affect a person's ability to interact with others. This can become a vicious cycle resulting in further decline in health. For this reason, the social management o...
Preprint
Full-text available
We present a set of capabilities allowing an agent planning with moral and social norms represented in temporal logic to respond to queries about its norms and behaviors in natural language, and for the human user to add and remove norms directly in natural language. The user may also pose hypothetical modifications to the agent's norms and inquire...
Preprint
Full-text available
We present an approach to generating natural language justifications of decisions derived from norm-based reasoning. Assuming an agent which maximally satisfies a set of rules specified in an object-oriented temporal logic, the user can ask factual questions (about the agent's rules, actions, and the extent to which the agent violated the rules) as...
Chapter
Full-text available
In typical human interactions emotional states are communicated via a variety of modalities such as auditory (through speech), visual (through facial expressions) and kinesthetic (through gestures). However, one or more modalities might be compromised in some situations, as in the case of facial masking in Parkinson’s disease (PD). In these cases,...
Chapter
Full-text available
We describe a theoretical framework and recent research on one key aspect of robot ethics: the development and implementation of a robot’s moral competence. As autonomous machines take on increasingly social roles in human communities, these machines need to have some level of moral competence to ensure safety, acceptance, and justified trust. We r...
Conference Paper
In typical human interactions emotional states are communicated via a variety of modalities such as auditory (through speech), visual (through facial expressions) and kinesthetic (through gestures). However, one or more modalities might be compromised in some situations , as in the case of facial masking in Parkinson's disease (PD). In these cases,...
Article
HRI researchers have made major strides in developing robotic architectures that are capable of reading a limited set of social cues and producing behaviors that enhance their likeability and feeling of comfort amongst humans. However, the cues in these models are fairly direct and the interactions largely dyadic. To capture the normative qualities...
Article
Full-text available
Anaphora resolution is a central problem in natural language understanding. We study a subclass of this problem involving object pronouns when they are used in simple imperative sentences (e.g., “pick it up.”). Specifically, we address cases where situational and contextual information is required to interpret these pronouns. Current state-of-the a...
Article
The "hard problem" in speech production is embodied in the cognitive process which selects the single, correct word that the speaker intends to utter from among multiple words activated by their shared semantic concept. Bilingual word selection is even harder because of the generally held assumption that concept selection also activates both of the...
Conference Paper
Full-text available
In typical human interactions emotional states are communicated via a variety of modalities such as auditory (through speech), visual (through facial expressions) and kinesthetic (through gestures). However, one or more modalities might be compromised in some situations , as in the case of facial masking in Parkinson's disease (PD). In these cases,...
Article
Full-text available
Individuals with Parkinson's disease (PD) often exhibit facial masking (hypomimia), which causes reduced facial expressiveness. This can make it difficult for those who interact with the person to correctly read their emotional state and can lead to problematic social and therapeutic interactions. In this article, we develop a probabilistic model fo...
Article
Full-text available
Background: As robots are increasingly designed for health management applications, it is critical to not only consider the effects robots will have on patients but also consider a patient's wider social network, including the patient's caregivers and health care providers, among others. Objective: In this paper we investigated how people evalua...
Conference Paper
Full-text available
Robots are machines and as such do not have gender. However, many of the gender-related perceptions and expectations formed in human-human interactions may be inadvertently and unreasonably transferred to interactions with social robots. In this paper, we investigate how gender effects in people's perception of robots and humans depend on their emo...
Chapter
Full-text available
Even though morally competent artificial agents have yet to emerge in society, we need insights from empirical science into how people will respond to such agents and how these responses should inform agent design. Three survey studies presented participants with an artificial intelligence (AI) agent, an autonomous drone, or a human drone pilot fac...
Preprint
UNSTRUCTURED As robots are increasingly designed for health management applications, it is critical to not only consider the effects robots will have on patients, but also a patient’s wider social network, including the patient’s caregivers and health care provides, among others. In this paper, we use a vignette-based study to investigate how a rob...
Preprint
Full-text available
HRI researchers have made major strides in developing robotic architectures that are capable of reading a limited set of social cues and producing behaviors that enhance their likeability and feeling of comfort amongst humans. However, the cues in these models are fairly direct and the interactions largely dyadic. To capture the normative qualities...
Article
Full-text available
Robots designed to interact with humans in realistic environments must be able to handle uncertainty with respect to the identities and properties of the people, places, and things found in their environments. When humans refer to these entities using under-specified language, robots must often generate clarification requests to determine which ent...
Conference Paper
Full-text available
Human behavior is frequently guided by social and moral norms, and no human community can exist without norms. Robots that enter human societies must therefore behave in norm-conforming ways as well. However, currently there is no solid cognitive or computational model available of how human norms are represented, activated, and learned. We provide...
Chapter
Full-text available
DIARC has been under development for over 15 years. Different from other cognitive architectures like SOAR or ACT-R, DIARC is an intrinsically component-based distributed architecture scheme that can be instantiated in many different ways. Moreover, DIARC has several distinguishing features, such as affect processing and deep natural language integ...
Chapter
Full-text available
What knowledge needs to be learned to acquire a novel task? What background knowledge does an agent need to use newly acquired knowledge effectively? This chapter considers the functional roles of knowledge in task learning. These roles of knowledge span interaction with other entities and the environment and core functional capabilities of the rea...
Conference Paper
Full-text available
We show how temporal and spatial information can be represented as stable patterns in a dynamical system. We describe a model in which category perception arises from the incremen-tal recognition of temporal patterns from sequences of inputs and this is accomplished by decoding a pool of recurrently connected artificial neurons which is called a ne...