
Cristian Ramirez-AtenciaUniversidad Politécnica de Madrid | UPM · E.T.S.I. de Sistemas Informáticos
Cristian Ramirez-Atencia
Doctor of Philosophy
About
26
Publications
10,024
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375
Citations
Citations since 2017
Introduction
My main research topic is Evolutionary Multi-Objective Optimization, focusing on the complexity of real-life problems, with several constraints, a limited time for solving the problem and decision support on the selection of the final solution
Additional affiliations
April 2019 - August 2020
Education
October 2014 - October 2018
September 2013 - September 2014
September 2008 - July 2013
Publications
Publications (26)
This paper examines several widespread assumptions about artificial intelligence, particularly machine learning, that are often taken as factual premises in discussions on the future of patent law in the wake of ‘artificial ingenuity’. The objective is to draw a more realistic and nuanced picture of the human-computer interaction in solving technic...
Abstract: The paper examines a set of assumptions about artificial intelligence, particularly machine learning, often taken as factual premises in discussions on the future of patent law in the wake of ‘artificial ingenuity’. The objective is to draw a more realistic and nuanced picture of the human-computer interaction in solving technical problem...
This paper presents a new variant of the Non-dominated Sorting Genetic Algorithm to solve Multimodal Multi-objective optimization problems. We introduce a novel method to augment the diversity of solutions in decision space by combining the Manhattan and crowding distance. In our experiments, we use six test problems with different levels of comple...
Over the last decade, Unmanned Aerial Vehicles (UAVs) have been extensively used in many commercial applications due to their manageability and risk avoidance. One of the main problems considered is the Mission Planning for multiple UAVs, where a solution plan must be found satisfying the different constraints of the problem. This problem has multi...
Real-world and complex problems have usually many objective functions that have to be optimized all at once. Over the last decades, Multi-Objective Evolutionary Algorithms (MOEAs) are designed to solve this kind of problems. Nevertheless, some problems have many objectives which lead to a large number of non-dominated solutions obtained by the opti...
Over the last decade, developments in unmanned aerial vehicles (UAVs) has greatly increased, and they are being used in many fields including surveillance, crisis management or automated mission planning. This last field implies the search of plans for missions with multiple tasks, UAVs and ground control stations; and the optimization of several o...
Unmanned Aerial Vehicles (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning (task allocation) and real-time replanning, which are highly useful to increase the auton...
Management and mission planning over a swarm of unmanned aerial vehicle (UAV) remains to date as a challenging research trend in what regards to this particular type of aircrafts. These vehicles are controlled by a number of ground control station (GCS), from which they are commanded to cooperatively perform different tasks in specific geographic a...
El auge actual de las capacidades de los vehículos aéreos no tripulados o drones ha propiciado la creación de nuevas aplicaciones comerciales para la industria o la defensa. Estos vehículos pueden utilizarse en muchos campos como la vigilancia, la gestión de desastres y crisis, la agricultura o la silvicultura entre otros, dado que evitan poner en...
Due to recent booming of unmanned air vehicles (UAVs) technologies, these are being used in many fields involving complex tasks. Some of them involve a high risk to the vehicle driver, such as fire monitoring and rescue tasks, which make UAVs excellent for avoiding human risks. Mission planning for UAVs is the process of planning the locations and...
The current boom of Unmanned Aerial Vehicles (UAVs) is increasing the number of potential industrial and research applications. One of the most demanded topics in this area is related to the automated planning of a UAVs swarm, controlled by one or several Ground Control Stations (GCSs). In this context, there are several variables that influence th...
The fast technological improvements in unmanned aerial vehicles (UAVs) has created new scenarios where a swarm of UAVs could operate in a distributed way. This swarm of vehicles needs to be controlled from a set of ground control stations, and new reliable mission planning systems, which should be able to handle the large amount of variables and co...
From the last few years the interest and repercussion on Unmanned Aerial Vehicle (UAV) technologies have been extended from pure military applications to industrial and societal applications. One of the basic tasks to any UAV problems is related to the Mission Planning. This problem is particularly complex when a set of UAVs is considered. In the f...
Due to the rapid development of the UAVs capabilities, these are being incorporated into many fields to perform increasingly complex tasks. Some of these tasks are becoming very important because they involve a high risk to the vehicle driver, such as detecting forest fires or rescue tasks, while using UAVs avoids risking human lives. Recent resear...
Mission Planning Problem for a large number of Unmanned Air Vehicles (UAV) consists of a set of locations to visit in different time windows, and the actions that the vehicle can perform based on its features such as the sensors, speed or fuel capacity. After formulating this problem as a Constraint Satisfaction Problem (CSP), we try to search the...
In order to achieve flow and increase player retention, it is important that games difficulty matches player skills. Being able to evaluate how people play a game is a crucial component for detecting gamers strategies in video-games. One of the main problems in player strategy detection is whether attributes selected to define strategies correctly...
Mission Planning for a large number of Unmanned Aerial Vehicles (UAVs) involves a set of locations to visit in different time intervals, and the actions that a vehicle must perform depending on its features and sensors. Analyzing how humans solve this problem is sometimes hard due to the complexity of the problem and the lack of data available. Thi...
The Multi-UAV Cooperative Mission Planning Problem (MCMPP) is a complex problem which can be represented with a lower or higher level of complexity. In this paper we present a MCMPP which is modelled as a Constraint Satisfaction Problem (CSP) with 5 increasing levels of complexity. Each level adds additional variables and constraints to the problem...
Mission Planning is a classical problem that has been traditionally studied in several cases from Robotics to Space missions. This kind of problems can be extremely difficult in real and dynamic scenarios. This paper provides a first analysis for mission planning to Unmanned Air Vehicles (UAVs), where sensors and other equipment of UAVs to perform...
The problem of Mission Planning for a large number of Unmanned Air Vehicles (UAV) can be formulated as a Temporal Constraint Satisfaction Problem (TCSP). It consists on a set of locations that should visit in different time windows, and the actions that the vehicle can perform based on its features such as the payload, speed or fuel capacity. In th...
Projects
Projects (2)
Design and develop a future UAS ground station demonstrator, beyond current products and a parallel Ph.D academic program around it
This coordinated project focuses on the ephemeral properties -those with a transitory nature- that may affect the functioning of distributed versions of bioinspired algorithms. The availability of highly-volatile heterogeneous computer resources capable of running software agents requires an appropriate design and implementation of algorithms. This will allow to make a proper use of the available resources while circumventing the potential problems that may produce such non-reliable systems. Among the desired features for the algorithms under consideration -that will potentially be run on non-dedicated local computers, remote devices, cloud systems, ubiquituous systems, etc.- we look for ephemerality-awareness, which is related to self-capability for understanding the underlying systems where the algorithm is run as well as taking decisions on how to proceed taking into account the non-reliable nature of the system.
Some of the relevant features that the so-adapted versions of bioinspired algorithm should feature are: (i) Inclusion (all nodes should have a meaningful contribution to the final result, and they should be incorporated to the distributed system in such a way that they do), (ii) Asynchrony (nodes communicate with the others without a fixed schedule due to their different performance), (iii) Resilience (the sudden disappearance of computing nodes must not destabilize the functioning of the algorithm), (iv) Emergence (the nature of the computational environment does not allow a centralized control and requires decentralized, emergent behavior), and (v) Self-adaptation (the algorithm should adapt itself to the changing computational landscape).
We aim to develop models and algorithms featuring these desired properties, while approaching specific problems where they can be tested. The goals of the project are therefore: (1) Use bioinspired algorithms to analyze, model and optimize ephemeral computation environments, and (2) Deploy bioinspired systems on ephemeral computing environments to solve complex problems. We will pursue the previous goals using an Open Science philosophy, thus leading to an additional added-value objective, namely (3) Bridge the gap between Science and Society. More precisely, the above goals substantiate in the following objectives of the project: (i) Design bioinspired algorithms adapted to complex ephemeral environments. (ii) Performance study and prediction in ephemeral environments. (iii) Develop game AI and procedural game-content generators in ephemeral environments. (iv) Study computational creativity in ephemeral computing environments. (v) Create workflows and raise awareness on Open Science.
The two application areas considered, namely computational creativity (where overall goals include analyzing and evolving the underlying social patterns of use and interactions, as well as making use of ephemeral properties of agents involved) and content generation in games (focusing on the automatic generation of diverse content, ranging from fixed components such as maps or levels, to emergent ingredients -e.g., narrative, or secondary goals- and the development of human-like non-player characters), constitute proofs-of-concept for the technologies developed and will provide results of stand-alone value. They are specific targets of the European research strategy and open important avenues for the technological transfer to industry.
KEY WORDS OF THE COORDINATED PROJECT: ephemeral computing, bioinspired algorithms, optimization, self-*, computational creativity, videogames, open science