Arthur Carvalho

Arthur Carvalho
Miami University | MU · Department of Information Systems & Analytics

PhD

About

43
Publications
17,732
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
469
Citations
Introduction
I am the Dinesh & Ila Paliwal Innovation Chair and an Associate Professor at Farmer School of Business, Miami University. My research interests lie at the intersection of Artificial Intelligence, Information Systems, and Decision Analysis. In particular, I work on the development and deployment of AI techniques and disruptive technologies aiming at improving business processes and decision-making.

Publications

Publications (43)
Article
Full-text available
Recent years have seen an increased interest in crowdsourcing as a way of obtaining information from a potentially large group of workers at a reduced cost. The crowdsourcing process, as we consider in this paper, is as follows: a requester hires a number of workers to work on a set of similar tasks. After completing the tasks, each worker reports...
Article
Full-text available
We study a problem where a new, unfamiliar group of agents has to decide how a joint reward should be shared among them. We focus on settings where the share that each agent receives depends on the evaluations of its peers concerning that agent's contribution to the group. We introduce a mechanism to elicit and aggregate evaluations as well as for...
Conference Paper
Full-text available
We propose a pooling method to aggregate expert opinions. Intuitively, it works as if the experts were continuously updating their opinions in order to accommodate the expertise of others. Each updated opinion takes the form of a linear opinion pool, where the weight that an expert assigns to a peer's opinion is inversely related to the distance be...
Article
Underdeveloped charging infrastructure is one of the main barriers to widespread electric vehicle (EV) adoption. Transforming parking lots into EV-enabled parking lots that provide parking and charging services is a solution to address the need for charging stations. Two challenges arise in this context: (1) how many parking spots should receive EV...
Article
This paper proposes and analyzes a methodology for extracting the underlying emotional dimensions connected to different textual data, including social-media posts and online reviews. Our experiments result in a coherent conclusion across all 16 studied datasets. In particular, the found orthogonal emotional dimensions are a combination of valence...
Article
Demand-side management solutions reward flexible customers for achieving desired goals. However, under price-based demand-response programs, uncoordinated load shifting among many customers may lead to rebound peaks, thus incurring financial costs on the energy service provider (ESP). This study addresses this issue from both the ESP (utility compa...
Article
We consider a newsvendor setting where the newsvendor elicits a demand forecast from an expert to determine the optimal inventory level for a product. Since the interests of both parties might not be aligned, we propose a proper scoring rule to elicit the expert's forecast that is tailored to the decision problem the newsvendor faces. Under the pro...
Article
Blockchain has been praised for providing the technical infrastructure that enables a group of self-interested entities to share data without relying on intermediaries. Technically, blockchain is a distributed and decentralized append-only database. This latter aspect leads to an important, yet overlooked governance issue, namely what should the ne...
Article
Full-text available
While the importance of physical (social) distancing in reducing the spread of COVID-19 has been well-documented, implementing similar controls in public transit remains an open question. For instance, in the United States, guidance for maximum seating capacity in single-destination public transit settings, such as school buses, is only dependent o...
Article
Full-text available
The ever-increasing reliance on loot boxes by the video game industry has attracted scrutiny from consumer groups and regulators. For example, this practice of selling random assortments of virtual items for a price has been criticized for its lack of transparency since, before purchasing a loot box, players do not necessarily know the possible ite...
Conference Paper
Full-text available
The use of outcome-contingent payments is a common approach when evaluating and rewarding forecasters. But since realized outcomes are only determined in the future, outcome-contingent payments naturally lead to trust issues in that a forecaster must trust the forecast requester to make a payment after a forecast has been reported. This scenario is...
Article
Electric vehicle (EV) owners enjoy many positive aspects when driving their cars, including low running costs and zero tailpipe gas emissions, which makes EVs a clean technology provided that they are sourced through renewable sources, e.g., biomass, solar power, or wind energy. However, their driving behaviour is often negatively affected by the s...
Article
In this work, a preference-based, demand response (DR) multi-objective optimization model based on real-time electricity price is presented to solve the problem of optimal residential load management. The purpose of such a model is threefold: 1) to minimize the costs associated with consumption; 2) to minimize the inconvenience caused to consumers;...
Conference Paper
Full-text available
Off-the-shelf technologies provided by major cloud platforms promise to facilitate and democratize the use of artificial intelligence techniques. Organizations can now apply highly sophisticated, pre-trained models in a variety of situations, such as when analyzing the sentiment behind social media posts. Among other uses, this enables organization...
Article
Since the seminal work by Hanson (2003), the Logarithmic Market Scoring Rule (LMSR) has become the de facto market-maker mechanism for prediction markets. We suggest in this paper three potential issues with centralized implementations of LMSR, which we refer to as the availability, security, and privacy problems. We also explain how a permissioned...
Article
Full-text available
The healthcare ecosystem continually produces huge volumes of structured and unstructured data. Cognitive computing, a new computing paradigm, promises to effectively help healthcare researchers and practitioners to derive precious information from data. Arguably, the most famous cognitive computing system is called IBM Watson, which has been adapt...
Article
Full-text available
Off-The-Shelf Artificial Intelligence Technologies for Sentiment and Emotion Analysis: A Tutorial on Using IBM Natural Language Processing was actually written by the following authors: Arthur Carvalho, Miami University - OxfordFollow Adam Levitt, Miami University Seth Levitt, Miami University Edward Khaddam, University of Tennessee John Benamati,...
Conference Paper
Full-text available
In this paper, we analyze the value of smart contracts and blockchains as an alternative to traditional contractual obligations. In particular, we start by exploring some of the advantages of these technologies, specifically the immutability of blockchains and automated contract remittance. We also discuss two critical shortcomings of decentralized...
Conference Paper
Full-text available
Cryptocurrencies have gained tremendous popularity over the past few years. The purpose of this study is to try to understand the factors that are driving cryptocurrency-related trading activities. Focusing on the well-established cryptocurrency called Bitcoin, we find that online search popularity and the volume of trade in unrelated stock markets...
Conference Paper
Full-text available
The quality of data sources is one of the biggest concerns regarding (big) data analytics. For example, humans can deliberately lie or behave strategically when reporting their beliefs/opinions in surveys and opinion polls, which results in data sets of low reliability. The issue of honest reporting of subjective data can, in theory, be tackled by...
Article
Full-text available
Scoring rules are traditional techniques to measure the association between a reported belief and an observed outcome. The condition that a scoring rule is proper means that an agent maximizes his expected score when he reports a belief that equals his true belief. The implicit assumption that the agent is risk neutral is, however, often unrealisti...
Article
Full-text available
Current trends suggest that there is a substantial increase in the overall usage of electric vehicles (EVs). This, in turn, is causing drastic changes in the transportation industry and, more broadly, in business, policy making, and society. One concrete challenge brought by the increase in the number of EVs is a higher demand for charging stations...
Article
Full-text available
The recent advent of electric vehicles (EVs) marks the beginning of a new positive era in the transportation sector. Although the environmental benefits of EVs are well-known today, planning and managing EV charging infrastructure are activities that are still not well-understood. In this paper, we are investigating how the so-called EV-enabled par...
Article
The logarithmic market scoring rule (LMSR) is now the de facto market-maker mechanism for prediction markets. We show how LMSR can have more representative final prices by simply imposing a participation structure where the market proceeds in rounds and, in each round, traders can only trade up to a fixed number of contracts. Focusing on markets ov...
Conference Paper
Full-text available
Current trends suggest that there is an increase in the overall usage of electric vehicles (EV). This, in turn, is causing drastic changes in the transportation industry and, more broadly, in business, policymaking and society. One concrete challenge brought by the increase in the number of EVs is a higher demand for charging stations. This paper p...
Conference Paper
Full-text available
The reduction of greenhouse gas emissions is seen as an important step towards environmental sustainability. Perhaps not surprising, many governments all around the world are providing incentives for consumers to buy electric vehicles (EVs). A positive response from consumers means that the demand for the charging infrastructure increases as well....
Article
Full-text available
We discuss payment structures that induce honest reporting of private information by risk-neutral agents in settings involving multiple-choice questions. Such payment structures do not rely on the existence of ground-truth answers, but instead they rely on the assumption that agents exhibit social projection. Social projection is a strong form of t...
Article
Full-text available
We present a study on the evolution of publications about applications of proper scoring rules. Specifically, we consider articles reporting the use of proper scoring rules when either measuring the accuracy of forecasts or for inducing honest reporting of private information within a certain context. Our analysis of a data set containing 201 artic...
Article
Full-text available
Incentive-compatible methods for eliciting beliefs, such as proper scoring rules, often rely on strong assumptions about how humans behave when making decisions under risk and uncertainty. For example, standard proper scoring rules assume that humans are risk neutral, an assumption that is often violated in practice. Under such an assumption, prope...
Conference Paper
Full-text available
Recent years have seen an increased interest in crowdsourcing as a way of obtaining information from a large group of workers at a reduced cost. In general, there are arguments for and against using multiple workers to perform a task. On the positive side, multiple workers bring different perspectives to the process, which may result in a more accu...
Article
Full-text available
Proper scoring rules are scoring methods that incentivize honest reporting of subjective probabilities, where an agent strictly maximizes his expected score by reporting his true belief. The implicit assumption behind proper scoring rules is that agents are risk neutral. Such an assumption is often unrealistic when agents are human beings. Modern t...
Article
Full-text available
The output-agreement method has been successfully used to reward agents in a variety of crowd-sourcing settings. This method consists of a simple payment function that randomly matches two agents' reported information and rewards agreement. In this letter, we discuss how the output-agreement method might induce honest behavior when there exists soc...
Conference Paper
Full-text available
We propose a reinforcement learning solution to the soccer dribbling task, a scenario in which a soccer agent has to go from the beginning to the end of a region keeping possession of the ball, as an adversary attempts to gain possession. While the adversary uses a stationary policy, the dribbler learns the best action to take at each decision poin...
Conference Paper
Full-text available
We study a problem where a group of agents has to decide how a joint reward should be shared among them. We focus on settings where the share that each agent receives depends on the subjective opinions of its peers concerning that agent's contribution to the group. To this end, we introduce a mechanism to elicit and aggregate subjective opinions as...
Conference Paper
Full-text available
We propose a cooperative coevolutionary genetic algorithm for learning Bayesian network structures from fully observable data sets. Since this problem can be decomposed into two dependent subproblems, that is to find an ordering of the nodes and an optimal connectivity matrix, our algorithm uses two subpopulations, each one representing a subtask....
Conference Paper
Full-text available
We study a problem where a group of agents has to decide how some fixed value should be shared among them. We are interested in settings where the share that each agent receives is based on how that agent is evaluated by other members of the group, where highly regarded agents receive a greater share compared to agents that are not well regarded. W...
Conference Paper
Full-text available
In soccer, scoring goals is a fundamental objective which depends on many conditions and constraints. Considering the RoboCup soccer 2D-simulator, this paper presents a data mining-based decision system to identify the best time and direction to kick the ball towards the goal to maximize the overall chances of scoring during a simulated soccer matc...
Conference Paper
Full-text available
The performance of a Multiobjective Evolutionary Algorithm (MOEA) is crucially dependent on the parameter setting of the operators. The most desired control of such parameters presents the characteristic of adaptiveness, i.e., the capacity of changing the value of the parameter, in distinct stages of the evolutionary process, using feedbacks from t...

Network

Cited By

Projects

Projects (2)
Project
We investigate how blockchain technology coupled with smart contracts can bring trust and transparency to different business processes and practices that are currently highly centralized and opaque.
Project
Electric vehicles (EVs) are drivers of change and innovation in both transportation and energy landcapes. The research goal of this project is to design and implement a computational framework for facilitating transformation of traditional parking lots, which offer business-as-usual parking service, into so-called EV-enabled parking lots (EVPLs), which offer not only the parking service but also the charging service as well.